SDS-2.2, Scalable Data Science

Archived YouTube video of this live unedited lab-lecture:

Hail Tutorial in Scala for Population Genomics ETL

Student Project

by Dmytro Kryvokhyzha and Yevgen Ryeznik

In this tutorial, we will analyze data from the 1000 Genomes Project as described in Analyzing 1000 Genomes with Spark and Hail except that we will use Scala instead of Python.

Hail uses Python wrapper on top of Apache Spark. We re-wrote the Analyzing 1000 Genomes with Spark and Hail tutorial in Scala with some modification and more up-to-date code as our course project for the Scalable Data Science 2.2 course.

We believe this tutorial will help to understand the code of Hail better and it will be helpful for those who plan to develop genomic analyses in Scala and contribute to the Hail project.

Introduction

Before we start, we would like to provide you a short introduction to how the genomic data is obtained and motivate the need to treat it as Big Data.

The importance of big data analyses in genomics is the best explained by this recent paper.

Big Data: Astronomical or Genomical?

Abstract

Genomics is a Big Data science and is going to get much bigger, very soon, but it is not known whether the needs of genomics will exceed other Big Data domains. Projecting to the year 2025, we compared genomics with three other major generators of Big Data: astronomy, YouTube, and Twitter. Our estimates show that genomics is a “four-headed beast” - it is either on par with or the most demanding of the domains analyzed here in terms of data acquisition, storage, distribution, and analysis. We discuss aspects of new technologies that will need to be developed to rise up and meet the computational challenges that genomics poses for the near future. Now is the time for concerted, community-wide planning for the “genomical” challenges of the next decade.

The plot shows the growth of DNA sequencing both in the total number of human genomes sequenced (left axis) as well as the worldwide annual sequencing capacity (right axis: Tera-basepairs (Tbp), Peta-basepairs (Pbp), Exa-basepairs (Ebp), Zetta-basepairs (Zbps)).

The price of genomic data production has also dropped dramatically in the recent years.

DNA sequencing

During the DNA sequencing procedure, DNA is chopped into small fragments and each fragment is then read by the sequencing machine. Using the variant sites in these DNA fragments (called reads), the overlap in these DNA reads can be found and a continuous genome sequence can be assembled.

However, the genome assembly from these short reads is not as trivial as it looks on this picture. So, these genomic reads are usually mapped to the reference genome that has been assembled already. You can see how this mapping looks in the cell below.

Aligning millions of small DNA sequences (reads) to a reference genome

You can obtain this picture by loading your alignment in BAM format to the Integrative Genomics Viewer (IGV)

The top panel shows the genomic position in the reference. Next, you can see the vertical bars indicating the depth of coverage in a given position. Those grey horizontal bars represent DNA reads. The grey color in a read means that an allele (nucleotide) is identical to the reference in that position. If the genotype in a certain position is different fro the reference, the alternative allele (nucleotide) is shown. For example, you can see the highlighted heterozygous position that has two alleles. The allele A is covered by 22 reads and it is the reference allele. The allele G is an alternative allele that is why it is designated in reads and it is covered by 15 reads.

Given this alignment, one can obtain a table of variants in the variant call format (VCF).

VCF in Hail

Hail uses the following scheme for the VCF.

Hail

Hail is an open-source, scalable framework for exploring and analyzing genomic data. Its functionality is exposed through Python and backed by distributed algorithms built on top of Apache Spark to efficiently analyze gigabyte-scale data on a laptop or terabyte-scale data on a cluster, without the need to manually chop up data or manage job failures. Users can script pipelines or explore data interactively through Jupyter notebooks that flow between Hail with methods for genomics, PySpark with scalable SQL and machine learning algorithms, and pandas with scikit-learn and Matplotlib for results that fit on one machine. Hail also provides a flexible domain language to express complex quality control and analysis pipelines with concise, readable code.

Scaling Genetic Data Analysis with Apache Spark

Cluster setup

First, download Hail source code and build hail-all-spark.jar file from the source code locally on your computer.

On Debian-based Linux, install compilers:

sudo apt-get install g++ cmake

On Mac OS X, install Xcode, available through the App Store, for the C++ compiler. CMake can be downloaded from the CMake website or through Homebrew. To install with Homebrew, run

 brew install cmake

Clone the Hail repository and build:

git clone --branch 0.1 https://github.com/broadinstitute/hail.git
cd hail
./gradlew -Dspark.version=2.0.2 shadowJar

You can also download the pre-built hail-all-spark.jar from here.

Upload the built build/libs/hail-all-spark.jar to Databricks Workspace > Shared > Libraries > Create Library and click Drop library JAR here to upload

Next click the Clusters icon on the left sidebar and then +Create Cluster. For Apache Spark Version, select Spark 2.0 (Auto-updating, Scala 2.11). In the Databricks cluster creation dialog, click on the Spark tab, and paste the text below into the Spark config box.

spark.hadoop.io.compression.codecs org.apache.hadoop.io.compress.DefaultCodec,is.hail.io.compress.BGzipCodec,org.apache.hadoop.io.compress.GzipCodec
spark.sql.files.openCostInBytes 1099511627776
spark.sql.files.maxPartitionBytes 1099511627776
spark.hadoop.mapreduce.input.fileinputformat.split.minsize 1099511627776
spark.hadoop.parquet.block.size 1099511627776

Go back to Workspace > Shared > Libraries click on the hail-all-spark.jar library and attach it to the created cluster.

Start the cluster and attach this notebook to it by clicking on your cluster name in menu Detached at the top left of this notebook.

Additional Cluster configuration

Some functions may not work and give the error: java.lang.NoClassDefFoundError: is/hail/asm4s/AsmFunction2. This is because Spark executors do not see the uploaded jar file.

To fix it, do the following steps.

Find out the temporary name assigned to your jar file by Databricks:

val hailJar = dbutils.fs.ls("/FileStore/jars/")
  .map(_.name)
  .filter(_.contains("hail_all_spark"))
  .headOption
  .getOrElse(sys.error("Failed to find hail jar, make sure that steps above are run"))
println(s"Found the jar: $hailJar")

Found the jar: 5bc47dbf_2252_429b_8c73_8ea474f94d4d-hail_all_spark-71440.jar
hailJar: String = 5bc47dbf_2252_429b_8c73_8ea474f94d4d-hail_all_spark-71440.jar

Copy this temporary jar file ($hailJar) to all executors:

dbutils.fs.put("/databricks/init/install_hail.sh", s"""
#!/bin/bash
mkdir -p /mnt/driver-daemon/jars
mkdir -p /mnt/jars/driver-daemon
cp /dbfs/FileStore/jars/$hailJar /mnt/driver-daemon/jars/ 
cp /dbfs/FileStore/jars/$hailJar /mnt/jars/driver-daemon/
""", true)

Wrote 302 bytes.
res14: Boolean = true

Restart the cluster and you are ready to go.

Processing

Import Hail and create Hail Context

import is.hail._
val hc = HailContext(sc)

2018-01-04 20:51:34 Hail: INFO: SparkUI: http://10.172.234.194:43914
2018-01-04 20:51:34 Hail: INFO: Running Hail version 0.1-5306854
import is.hail._
hc: is.hail.HailContext = is.hail.HailContext@1ca86921

Specify the path to files

These files are already uploaded and available in Databricks. If you decide to use your own files, please upload them to Databricks and move to the dbfs file system.

val vcf_path =  "/databricks-datasets/hail/data-001/1kg_sample.vcf.bgz"
val annotation_path = "/databricks-datasets/hail/data-001/1kg_annotations.txt"

vcf_path: String = /databricks-datasets/hail/data-001/1kg_sample.vcf.bgz
annotation_path: String = /databricks-datasets/hail/data-001/1kg_annotations.txt
purcell_5k_path: String = /databricks-datasets/hail/data-001/purcell5k.interval_list

Import the VCF file

var vds = hc.importVCF(vcf_path) // if input.bgz doesn't work, try to load uncompressed data.

2018-01-04 20:51:36 Hail: INFO: No multiallelics detected.
2018-01-04 20:51:36 Hail: INFO: Coerced sorted dataset
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(HG04171,null), (HG04176,null), (HG04182,null), (HG04186,null), (HG04189,null), (HG04194,null), (HG04195,null), (HG04210,null), (HG04219,null), (HG04225,null), (HG04229,null), (HG04235,null), (NA06989,null), (NA07000,null), (NA07037,null), (NA07357,null), (NA10847,null), (NA10851,null), (NA11840,null), (NA11894,null), (NA11918,null), (NA11920,null), (NA11932,null), (NA11933,null), (NA11992,null), (NA11994,null), (NA12046,null), (NA12156,null), (NA12272,null), (NA12282,null), (NA12283,null), (NA12340,null), (NA12347,null), (NA12400,null), (NA12546,null), (NA12717,null), (NA12749,null), (NA12751,null), (NA12760,null), (NA12761,null), (NA12814,null), (NA12830,null), (NA12890,null), (NA18488,null), (NA18505,null), (NA18510,null), (NA18526,null), (NA18533,null), (NA18535,null), (NA18536,null), (NA18542,null), (NA18550,null), (NA18552,null), (NA18558,null), (NA18560,null), (NA18571,null), (NA18577,null), (NA18582,null), (NA18595,null), (NA18596,null), (NA18603,null), (NA18608,null), (NA18609,null), (NA18610,null), (NA18613,null), (NA18615,null), (NA18618,null), (NA18620,null), (NA18622,null), (NA18623,null), (NA18624,null), (NA18626,null), (NA18636,null), (NA18638,null), (NA18639,null), (NA18641,null), (NA18646,null), (NA18648,null), (NA18740,null), (NA18867,null), (NA18871,null), (NA18874,null), (NA18912,null), (NA18915,null), (NA18933,null), (NA18949,null), (NA18950,null), (NA18951,null), (NA18953,null), (NA18956,null), (NA18957,null), (NA18964,null), (NA18970,null), (NA18975,null), (NA18978,null), (NA18981,null), (NA18982,null), (NA18983,null), (NA18985,null), (NA18987,null), (NA18990,null), (NA18991,null), (NA18999,null), (NA19003,null), (NA19006,null), (NA19007,null), (NA19010,null), (NA19011,null), (NA19024,null), (NA19026,null), (NA19031,null), (NA19037,null), (NA19041,null), (NA19055,null), (NA19057,null), (NA19058,null), (NA19059,null), (NA19060,null), (NA19062,null), (NA19063,null), (NA19064,null), (NA19065,null), (NA19079,null), (NA19082,null), (NA19086,null), (NA19095,null), (NA19102,null), (NA19119,null), (NA19129,null), (NA19147,null), (NA19159,null), (NA19172,null), (NA19185,null), (NA19189,null), (NA19197,null), (NA19200,null), (NA19238,null), (NA19247,null), (NA19248,null), (NA19257,null), (NA19315,null), (NA19320,null), (NA19332,null), (NA19338,null), (NA19372,null), (NA19375,null), (NA19379,null), (NA19384,null), (NA19393,null), (NA19397,null), (NA19401,null), (NA19404,null), (NA19435,null), (NA19443,null), (NA19446,null), (NA19449,null), (NA19455,null), (NA19457,null), (NA19466,null), (NA19468,null), (NA19471,null), (NA19473,null), (NA19474,null), (NA19625,null), (NA19655,null), (NA19663,null), (NA19681,null), (NA19703,null), (NA19707,null), (NA19711,null), (NA19716,null), (NA19717,null), (NA19722,null), (NA19728,null), (NA19731,null), (NA19747,null), (NA19764,null), (NA19770,null), (NA19773,null), (NA19776,null), (NA19777,null), (NA19782,null), (NA19785,null), (NA19788,null), (NA19819,null), (NA19834,null), (NA19835,null), (NA19917,null), (NA19921,null), (NA19982,null), (NA19984,null), (NA20276,null), (NA20281,null), (NA20298,null), (NA20321,null), (NA20336,null), (NA20342,null), (NA20351,null), (NA20412,null), (NA20506,null), (NA20507,null), (NA20509,null), (NA20512,null), (NA20514,null), (NA20517,null), (NA20518,null), (NA20525,null), (NA20531,null), (NA20532,null), (NA20536,null), (NA20539,null), (NA20544,null), (NA20588,null), (NA20589,null), (NA20753,null), (NA20756,null), (NA20758,null), (NA20765,null), (NA20773,null), (NA20774,null), (NA20785,null), (NA20786,null), (NA20798,null), (NA20801,null), (NA20803,null), (NA20807,null), (NA20814,null), (NA20815,null), (NA20818,null), (NA20821,null), (NA20846,null), (NA20847,null), (NA20851,null), (NA20858,null), (NA20863,null), (NA20881,null), (NA20886,null), (NA20890,null), (NA20898,null), (NA20900,null), (NA20908,null), (NA20910,null), (NA21086,null), (NA21088,null), (NA21091,null), (NA21094,null), (NA21097,null), (NA21101,null), (NA21104,null), (NA21109,null), (NA21111,null), (NA21114,null), (NA21119,null), (NA21120,null), (NA21123,null), (NA21125,null), (NA21128,null), (NA21130,null), (NA21133,null), (NA21137,null)), globalAnnotation=null, wasSplit=true)

Split multi-allelic variants

This method splits multi-allelic variants into biallelic variants. For example, the variant 1:1000:A:T,C would become two variants: 1:1000:A:T and 1:1000:A:C.

vds = vds.splitMulti()

2018-01-04 20:51:36 Hail: WARN: called redundant split on an already split VDS
vds: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Empty,Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}},Empty,Genotype,true,false,false), rdd=OrderedRDD[44] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00114, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00150, HG00151, HG00159, HG00181, HG00182, HG00183, HG00185, HG00232, HG00235, HG00238, HG00239, HG00240, HG00242, HG00243, HG00244, HG00245, HG00246, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00269, HG00271, HG00272, HG00273, HG00280, HG00290, HG00304, HG00311, HG00321, HG00323, HG00324, HG00326, HG00332, HG00334, HG00343, HG00356, HG00362, HG00367, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00565, HG00566, HG00583, HG00584, HG00592, HG00593, HG00598, HG00620, HG00635, HG00650, HG00654, HG00675, HG00701, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG00879, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01168, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01437, HG01438, HG01464, HG01474, HG01479, HG01488, HG01501, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01672, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01989, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03022, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12272, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, 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NA19455, NA19457, NA19466, NA19468, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19711, NA19716, NA19717, NA19722, NA19728, NA19731, NA19747, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20851, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21123, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=710, 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(NA21104,null), (NA21109,null), (NA21111,null), (NA21114,null), (NA21119,null), (NA21120,null), (NA21123,null), (NA21125,null), (NA21128,null), (NA21130,null), (NA21133,null), (NA21137,null)), globalAnnotation=null, wasSplit=true)

Annotate samples

This step will load information on each sample from the sample annotations file.

First, we import the annotation table. impute=true will infer column types automatically.

val table = hc.importTable(annotation_path, impute=true).keyBy("Sample")

2018-01-04 20:51:37 Hail: INFO: Reading table to impute column types
2018-01-04 20:51:37 Hail: INFO: Finished type imputation
  Loading column `Sample' as type String (imputed)
  Loading column `Population' as type String (imputed)
  Loading column `SuperPopulation' as type String (imputed)
  Loading column `isFemale' as type Boolean (imputed)
  Loading column `PurpleHair' as type Boolean (imputed)
  Loading column `CaffeineConsumption' as type Double (imputed)
table: is.hail.keytable.KeyTable = KeyTable(is.hail.HailContext@1ca86921,MapPartitionsRDD[51] at map at HailContext.scala:345,Struct{Sample:String,Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double},[Ljava.lang.String;@1e4520b9)

Print the annotation table

display(table.toDF(hc.sqlContext))

Apply the annotation schema to the VDS

vds = vds.annotateSamplesTable(table, root="sa")

vds: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}},Empty,Genotype,true,false,false), rdd=OrderedRDD[44] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00114, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00150, HG00151, HG00159, HG00181, HG00182, HG00183, HG00185, HG00232, HG00235, HG00238, HG00239, HG00240, HG00242, HG00243, HG00244, HG00245, HG00246, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00269, HG00271, HG00272, HG00273, HG00280, HG00290, HG00304, HG00311, HG00321, HG00323, HG00324, HG00326, HG00332, HG00334, HG00343, HG00356, HG00362, HG00367, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00565, HG00566, HG00583, HG00584, HG00592, HG00593, HG00598, HG00620, HG00635, HG00650, HG00654, HG00675, HG00701, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG00879, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01168, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01437, HG01438, HG01464, HG01474, HG01479, HG01488, HG01501, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01672, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01989, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03022, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12272, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18609, NA18610, NA18613, NA18615, NA18618, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18871, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19082, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19468, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19711, NA19716, NA19717, NA19722, NA19728, NA19731, NA19747, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20851, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21123, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=710, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0], [GBR,EUR,true,false,59.0], [GBR,EUR,false,false,77.0], [GBR,EUR,false,true,72.0], [GBR,EUR,false,true,71.0], [GBR,EUR,false,false,71.0], [GBR,EUR,false,true,70.0], [GBR,EUR,true,true,68.0], [GBR,EUR,true,true,67.0], [GBR,EUR,false,false,72.0], [GBR,EUR,false,false,74.0], [GBR,EUR,false,false,78.0], [GBR,EUR,false,false,77.0], [GBR,EUR,true,true,64.0], [GBR,EUR,false,false,69.0], [GBR,EUR,false,false,64.0], [FIN,EUR,false,true,62.0], [FIN,EUR,false,false,72.0], [FIN,EUR,false,false,69.0], [FIN,EUR,false,true,70.0], [GBR,EUR,true,true,69.0], [GBR,EUR,true,true,73.0], [GBR,EUR,true,true,66.0], [GBR,EUR,true,true,64.0], [GBR,EUR,true,false,65.0], [GBR,EUR,false,false,70.0], [GBR,EUR,false,true,63.0], [GBR,EUR,false,false,73.0], [GBR,EUR,true,false,72.0], [GBR,EUR,false,false,72.0], [GBR,EUR,true,false,67.0], [GBR,EUR,true,false,64.0], [GBR,EUR,true,true,68.0], [GBR,EUR,true,true,64.0], [GBR,EUR,true,true,66.0], [GBR,EUR,false,true,73.0], [FIN,EUR,true,true,67.0], [FIN,EUR,false,false,73.0], [FIN,EUR,true,true,71.0], [FIN,EUR,false,true,67.0], [FIN,EUR,false,false,70.0], [FIN,EUR,false,false,71.0], [FIN,EUR,true,true,65.0], [FIN,EUR,false,true,71.0], [FIN,EUR,false,false,79.0], [FIN,EUR,true,false,58.0], [FIN,EUR,true,true,61.0], [FIN,EUR,true,false,64.0], [FIN,EUR,true,true,60.0], [FIN,EUR,true,false,68.0], [FIN,EUR,true,true,64.0], [FIN,EUR,true,true,74.0], [FIN,EUR,true,true,63.0], [FIN,EUR,true,false,66.0], [FIN,EUR,false,true,71.0], [CHS,EAS,true,false,64.0], [CHS,EAS,true,true,68.0], [CHS,EAS,true,true,70.0], [CHS,EAS,true,true,66.0], [CHS,EAS,true,false,64.0], [CHS,EAS,false,true,71.0], [CHS,EAS,true,false,64.0], [CHS,EAS,false,true,75.0], [CHS,EAS,false,false,79.0], [CHS,EAS,false,true,77.0], [CHS,EAS,true,true,69.0], [CHS,EAS,false,false,69.0], [CHS,EAS,true,true,65.0], [CHS,EAS,false,true,76.0], [CHS,EAS,true,true,62.0], [CHS,EAS,false,true,65.0], [CHS,EAS,true,true,69.0], [CHS,EAS,false,false,71.0], [CHS,EAS,true,false,65.0], [CHS,EAS,false,true,66.0], [CHS,EAS,true,false,61.0], [CHS,EAS,true,false,69.0], [CHS,EAS,false,true,70.0], [CHS,EAS,true,true,66.0], [CHS,EAS,true,false,66.0], [CHS,EAS,false,true,67.0], [CHS,EAS,true,false,70.0], [CHS,EAS,false,true,70.0], [CHS,EAS,true,true,65.0], [CHS,EAS,false,true,70.0], [PUR,AMR,true,true,65.0], [CDX,EAS,true,true,64.0], [CDX,EAS,true,true,63.0], [CDX,EAS,true,false,65.0], [CDX,EAS,true,true,74.0], [PUR,AMR,false,false,74.0], [PUR,AMR,false,false,65.0], [PUR,AMR,true,true,66.0], [PUR,AMR,false,false,68.0], [PUR,AMR,true,false,69.0], [PUR,AMR,true,false,62.0], [PUR,AMR,false,false,73.0], [PUR,AMR,false,false,71.0], [PUR,AMR,true,true,61.0], [PUR,AMR,false,false,74.0], [CLM,AMR,false,true,61.0], [CLM,AMR,true,true,65.0], [CLM,AMR,false,false,73.0], [CLM,AMR,true,false,66.0], [CLM,AMR,false,false,69.0], [PUR,AMR,true,false,60.0], [PUR,AMR,false,true,80.0], [PUR,AMR,true,true,64.0], [PUR,AMR,true,true,67.0], [PUR,AMR,false,false,70.0], [PUR,AMR,true,false,72.0], [PUR,AMR,true,true,65.0], [PUR,AMR,true,true,60.0], [CLM,AMR,true,true,66.0], [CLM,AMR,false,true,71.0], [CLM,AMR,false,false,67.0], [CLM,AMR,true,true,63.0], [CLM,AMR,true,false,68.0], [PUR,AMR,false,false,70.0], [PUR,AMR,false,false,72.0], [PUR,AMR,true,false,65.0], [GBR,EUR,false,false,76.0], [CLM,AMR,false,true,75.0], [CLM,AMR,false,true,75.0], [CLM,AMR,false,false,72.0], [CLM,AMR,true,true,63.0], [CLM,AMR,false,true,69.0], [CLM,AMR,true,false,66.0], [CLM,AMR,true,false,62.0], [CLM,AMR,true,false,67.0], [PUR,AMR,false,false,76.0], [PUR,AMR,false,false,69.0], [CLM,AMR,false,false,71.0], [CLM,AMR,true,false,72.0], [CLM,AMR,false,false,67.0], [CLM,AMR,true,false,63.0], [CLM,AMR,false,true,72.0], [CLM,AMR,false,true,73.0], [IBS,EUR,true,false,72.0], [IBS,EUR,false,true,72.0], [IBS,EUR,false,false,69.0], [IBS,EUR,true,false,63.0], [IBS,EUR,true,true,58.0], [IBS,EUR,true,true,64.0], [CLM,AMR,false,false,73.0], [PEL,AMR,false,true,72.0], [PJL,SAS,false,true,66.0], [KHV,EAS,true,true,62.0], [IBS,EUR,false,false,59.0], [IBS,EUR,false,false,73.0], [IBS,EUR,false,true,68.0], [IBS,EUR,true,false,62.0], [IBS,EUR,false,false,68.0], [IBS,EUR,false,true,70.0], [IBS,EUR,false,true,77.0], [IBS,EUR,false,true,62.0], [IBS,EUR,false,false,69.0], [IBS,EUR,false,false,72.0], [IBS,EUR,false,true,72.0], [IBS,EUR,true,false,63.0], [IBS,EUR,false,true,66.0], [IBS,EUR,false,true,71.0], [IBS,EUR,true,false,67.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,true,67.0], [CDX,EAS,true,true,64.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,false,64.0], [CDX,EAS,false,false,69.0], [CDX,EAS,true,false,64.0], [CDX,EAS,true,false,62.0], [CDX,EAS,false,true,71.0], [KHV,EAS,false,false,74.0], [KHV,EAS,true,false,68.0], [KHV,EAS,false,false,75.0], [KHV,EAS,false,false,68.0], [KHV,EAS,false,false,71.0], [KHV,EAS,true,true,66.0], [KHV,EAS,false,true,65.0], [ACB,AFR,true,false,71.0], [PEL,AMR,false,false,66.0], [PEL,AMR,true,false,64.0], [ACB,AFR,false,false,67.0], [PEL,AMR,false,true,75.0], [PEL,AMR,false,true,75.0], [PEL,AMR,false,false,76.0], [PEL,AMR,true,false,69.0], [PEL,AMR,true,false,69.0], [PEL,AMR,false,true,74.0], [PEL,AMR,true,true,60.0], [PEL,AMR,false,false,70.0], [PEL,AMR,true,true,68.0], [PEL,AMR,false,false,71.0], [PEL,AMR,true,true,67.0], [PEL,AMR,false,false,80.0], [PEL,AMR,false,true,74.0], [ACB,AFR,true,false,61.0], [PEL,AMR,true,false,69.0], [PEL,AMR,false,false,68.0], [KHV,EAS,false,true,76.0], [KHV,EAS,true,true,64.0], [KHV,EAS,true,false,65.0], [KHV,EAS,false,true,68.0], [KHV,EAS,false,true,76.0], [KHV,EAS,true,true,66.0], [ACB,AFR,false,false,68.0], [KHV,EAS,true,true,67.0], [KHV,EAS,false,true,69.0], [KHV,EAS,true,true,64.0], [KHV,EAS,false,false,67.0], [KHV,EAS,true,true,67.0], [KHV,EAS,true,true,67.0], [PEL,AMR,true,true,68.0], [ACB,AFR,true,false,66.0], [PEL,AMR,true,false,66.0], [PEL,AMR,false,true,64.0], [ACB,AFR,true,true,63.0], [ACB,AFR,true,true,65.0], [KHV,EAS,true,true,67.0], [KHV,EAS,true,false,69.0], [KHV,EAS,true,true,68.0], [KHV,EAS,true,true,63.0], [ACB,AFR,false,true,71.0], [PEL,AMR,false,false,69.0], [CDX,EAS,true,true,62.0], [CDX,EAS,true,false,67.0], [CDX,EAS,true,true,65.0], [IBS,EUR,true,true,62.0], [PEL,AMR,true,true,68.0], [ACB,AFR,false,true,71.0], [PEL,AMR,false,true,66.0], [PEL,AMR,false,true,73.0], [PEL,AMR,false,true,65.0], [PEL,AMR,false,true,67.0], [ACB,AFR,false,true,70.0], [ACB,AFR,true,true,67.0], [ACB,AFR,false,false,71.0], [PEL,AMR,true,true,68.0], [PEL,AMR,true,false,66.0], [PEL,AMR,false,true,61.0], [ACB,AFR,true,true,62.0], [ACB,AFR,true,true,61.0], [ACB,AFR,true,false,70.0], [ACB,AFR,true,true,62.0], [ACB,AFR,false,true,66.0], [ACB,AFR,true,false,66.0], [ACB,AFR,false,true,59.0], [CDX,EAS,false,false,62.0], [CDX,EAS,false,false,72.0], [CDX,EAS,false,true,71.0], [CDX,EAS,false,true,69.0], [CDX,EAS,false,true,74.0], [CDX,EAS,false,true,66.0], [CDX,EAS,false,true,70.0], [CDX,EAS,false,false,71.0], [CDX,EAS,false,false,71.0], [ACB,AFR,true,false,61.0], [ACB,AFR,false,false,72.0], [ACB,AFR,false,true,73.0], [ACB,AFR,true,true,68.0], [ACB,AFR,false,true,70.0], [ACB,AFR,false,true,72.0], [PJL,SAS,true,true,66.0], [ACB,AFR,true,false,63.0], [ACB,AFR,true,false,65.0], [KHV,EAS,false,false,66.0], [ACB,AFR,true,false,61.0], [ACB,AFR,false,false,70.0], [ACB,AFR,true,true,67.0], [ACB,AFR,false,false,70.0], [GWD,AFR,true,false,66.0], [GWD,AFR,true,false,67.0], [ACB,AFR,true,true,66.0], [ACB,AFR,true,true,57.0], [GWD,AFR,true,true,71.0], [GWD,AFR,true,true,68.0], [PJL,SAS,true,true,67.0], [GWD,AFR,false,false,72.0], [GWD,AFR,true,true,72.0], [GWD,AFR,false,true,73.0], [GWD,AFR,false,false,74.0], [PJL,SAS,true,false,66.0], [PJL,SAS,false,true,69.0], [PJL,SAS,true,true,67.0], [PJL,SAS,false,true,70.0], [PJL,SAS,false,false,72.0], [GWD,AFR,false,true,66.0], [GWD,AFR,true,false,68.0], [GWD,AFR,false,true,68.0], [GWD,AFR,true,false,66.0], [PJL,SAS,true,false,69.0], [PJL,SAS,false,false,72.0], [PJL,SAS,true,false,70.0], [PJL,SAS,false,false,69.0], [GWD,AFR,true,false,72.0], [PJL,SAS,false,false,71.0], [PJL,SAS,true,true,64.0], [PJL,SAS,true,false,73.0], [GWD,AFR,true,true,64.0], [GWD,AFR,false,true,67.0], [GWD,AFR,true,false,69.0], [GWD,AFR,false,true,68.0], [PJL,SAS,false,false,73.0], [PJL,SAS,false,false,72.0], [PJL,SAS,true,true,62.0], [PJL,SAS,false,false,65.0], [GWD,AFR,false,false,70.0], [GWD,AFR,false,false,66.0], [GWD,AFR,true,true,65.0], [GWD,AFR,false,false,68.0], [GWD,AFR,true,true,66.0], [GWD,AFR,false,false,69.0], [GWD,AFR,true,false,64.0], [GWD,AFR,false,true,72.0], [GWD,AFR,false,true,64.0], [GWD,AFR,true,true,68.0], [GWD,AFR,true,false,67.0], [GWD,AFR,false,true,69.0], [GWD,AFR,false,true,73.0], [ESN,AFR,false,false,67.0], [ESN,AFR,false,true,70.0], [ESN,AFR,false,false,64.0], [ESN,AFR,false,true,66.0], [ESN,AFR,true,true,66.0], [ESN,AFR,true,true,63.0], [ESN,AFR,false,false,63.0], [GWD,AFR,true,false,64.0], [BEB,SAS,false,false,69.0], [PJL,SAS,false,false,68.0], [PJL,SAS,true,true,66.0], [GWD,AFR,false,true,65.0], [GWD,AFR,true,true,67.0], [GWD,AFR,true,false,61.0], [MSL,AFR,false,false,71.0], [MSL,AFR,false,true,71.0], [MSL,AFR,false,false,68.0], [MSL,AFR,true,true,60.0], [MSL,AFR,true,true,61.0], [ESN,AFR,false,true,65.0], [ESN,AFR,true,true,66.0], [ESN,AFR,false,false,71.0], [ESN,AFR,true,true,60.0], [ESN,AFR,false,false,66.0], [ESN,AFR,false,true,64.0], [ESN,AFR,true,true,65.0], [ESN,AFR,false,true,74.0], [ESN,AFR,true,false,64.0], [ESN,AFR,false,true,69.0], [ESN,AFR,false,false,71.0], [MSL,AFR,false,false,70.0], [PJL,SAS,false,true,71.0], [GWD,AFR,false,true,71.0], [GWD,AFR,true,false,66.0], [GWD,AFR,true,false,67.0], [GWD,AFR,false,false,71.0], [GWD,AFR,true,false,62.0], [ESN,AFR,false,false,65.0], [ESN,AFR,true,true,65.0], [ESN,AFR,false,false,74.0], [ESN,AFR,true,true,69.0], [ESN,AFR,false,false,69.0], [ESN,AFR,true,false,64.0], [ESN,AFR,false,false,65.0], [ESN,AFR,true,false,68.0], [ESN,AFR,true,false,62.0], [ESN,AFR,false,false,60.0], [MSL,AFR,false,false,67.0], [MSL,AFR,false,false,63.0], [MSL,AFR,false,false,62.0], [MSL,AFR,true,false,61.0], [MSL,AFR,true,false,65.0], [MSL,AFR,true,false,67.0], [MSL,AFR,false,true,74.0], [MSL,AFR,true,true,59.0], [PJL,SAS,true,true,62.0], [ESN,AFR,true,false,65.0], [ESN,AFR,true,false,56.0], [ESN,AFR,false,true,69.0], [ESN,AFR,false,false,68.0], [MSL,AFR,false,false,75.0], [MSL,AFR,true,true,69.0], [MSL,AFR,false,true,70.0], [MSL,AFR,true,false,65.0], [BEB,SAS,false,false,68.0], [BEB,SAS,true,true,65.0], [BEB,SAS,true,false,66.0], [PJL,SAS,false,true,65.0], [PJL,SAS,true,false,60.0], [PJL,SAS,false,true,70.0], [STU,SAS,true,false,62.0], [STU,SAS,false,false,64.0], [PJL,SAS,true,false,62.0], [STU,SAS,true,true,63.0], [PJL,SAS,true,false,69.0], [ITU,SAS,false,false,64.0], [ITU,SAS,false,true,66.0], [STU,SAS,false,true,65.0], [PJL,SAS,true,false,60.0], [PJL,SAS,false,false,73.0], [ITU,SAS,true,false,62.0], [ITU,SAS,true,true,64.0], [ITU,SAS,false,false,72.0], [ITU,SAS,false,true,69.0], [BEB,SAS,true,false,70.0], [BEB,SAS,true,true,63.0], [BEB,SAS,false,false,62.0], [BEB,SAS,false,false,67.0], [BEB,SAS,false,true,76.0], [BEB,SAS,true,false,65.0], [STU,SAS,false,false,59.0], [STU,SAS,true,false,71.0], [STU,SAS,true,true,58.0], [ITU,SAS,true,false,61.0], [ITU,SAS,false,false,65.0], [ITU,SAS,true,false,65.0], [ITU,SAS,false,false,63.0], [STU,SAS,true,true,61.0], [STU,SAS,true,true,68.0], [STU,SAS,false,true,70.0], [STU,SAS,false,false,66.0], [BEB,SAS,false,true,64.0], [BEB,SAS,true,false,70.0], [BEB,SAS,false,false,68.0], [BEB,SAS,true,true,62.0], [BEB,SAS,true,false,64.0], [STU,SAS,false,true,67.0], [STU,SAS,true,true,63.0], [STU,SAS,true,false,69.0], [STU,SAS,true,true,66.0], [STU,SAS,true,true,64.0], [ITU,SAS,true,true,61.0], [ITU,SAS,false,false,63.0], [STU,SAS,true,false,64.0], [STU,SAS,false,true,69.0], [ITU,SAS,false,true,69.0], [ITU,SAS,true,false,62.0], [STU,SAS,true,false,68.0], [ITU,SAS,true,true,64.0], [ITU,SAS,true,true,66.0], [ITU,SAS,false,false,74.0], [ITU,SAS,true,true,57.0], [ITU,SAS,true,true,64.0], [ITU,SAS,false,false,58.0], [STU,SAS,false,true,67.0], [BEB,SAS,false,false,67.0], [BEB,SAS,true,true,65.0], [BEB,SAS,false,false,59.0], [BEB,SAS,false,false,69.0], [BEB,SAS,false,true,69.0], [BEB,SAS,true,true,70.0], [BEB,SAS,false,false,71.0], [BEB,SAS,false,false,69.0], [BEB,SAS,true,true,70.0], [BEB,SAS,true,false,66.0], [BEB,SAS,false,false,66.0], [BEB,SAS,true,false,65.0], [STU,SAS,false,false,65.0], [ITU,SAS,false,false,66.0], [ITU,SAS,false,true,68.0], [STU,SAS,false,false,70.0], [ITU,SAS,false,false,65.0], [CEU,EUR,true,true,61.0], [CEU,EUR,true,false,60.0], [CEU,EUR,true,true,60.0], [CEU,EUR,false,true,71.0], [CEU,EUR,true,true,66.0], [CEU,EUR,false,false,74.0], [CEU,EUR,true,true,67.0], [CEU,EUR,true,false,61.0], [CEU,EUR,true,false,61.0], [CEU,EUR,true,false,65.0], [CEU,EUR,false,true,62.0], [CEU,EUR,true,true,68.0], [CEU,EUR,false,true,74.0], [CEU,EUR,false,false,74.0], [CEU,EUR,true,false,70.0], [CEU,EUR,true,false,64.0], [CEU,EUR,false,true,73.0], [CEU,EUR,false,false,61.0], [CEU,EUR,true,true,65.0], [CEU,EUR,false,false,66.0], [CEU,EUR,false,false,70.0], [CEU,EUR,true,true,63.0], [CEU,EUR,false,true,57.0], [CEU,EUR,true,true,73.0], [CEU,EUR,true,false,63.0], [CEU,EUR,true,true,64.0], [CEU,EUR,false,false,63.0], [CEU,EUR,true,true,64.0], [CEU,EUR,false,true,65.0], [CEU,EUR,true,true,64.0], [CEU,EUR,true,true,64.0], [YRI,AFR,true,false,66.0], [YRI,AFR,true,false,61.0], [YRI,AFR,false,true,67.0], [CHB,EAS,true,false,63.0], [CHB,EAS,true,false,62.0], [CHB,EAS,true,true,64.0], [CHB,EAS,false,true,67.0], [CHB,EAS,true,false,55.0], [CHB,EAS,true,true,66.0], [CHB,EAS,true,true,61.0], [CHB,EAS,false,true,73.0], [CHB,EAS,true,false,61.0], [CHB,EAS,true,true,67.0], [CHB,EAS,true,true,59.0], [CHB,EAS,true,false,60.0], [CHB,EAS,true,true,57.0], [CHB,EAS,true,true,65.0], [CHB,EAS,false,true,65.0], [CHB,EAS,false,false,73.0], [CHB,EAS,false,true,73.0], [CHB,EAS,true,false,68.0], [CHB,EAS,false,false,73.0], [CHB,EAS,true,false,64.0], [CHB,EAS,true,false,64.0], [CHB,EAS,false,true,72.0], [CHB,EAS,false,true,69.0], [CHB,EAS,false,true,66.0], [CHB,EAS,false,false,72.0], [CHB,EAS,true,false,59.0], [CHB,EAS,false,false,73.0], [CHB,EAS,false,true,73.0], [CHB,EAS,false,true,74.0], [CHB,EAS,true,false,67.0], [CHB,EAS,true,true,66.0], [CHB,EAS,false,true,65.0], [CHB,EAS,false,true,65.0], [YRI,AFR,true,false,65.0], [YRI,AFR,false,false,72.0], [YRI,AFR,false,true,64.0], [YRI,AFR,true,false,67.0], [YRI,AFR,false,true,69.0], [YRI,AFR,true,true,64.0], [JPT,EAS,true,true,64.0], [JPT,EAS,true,true,68.0], [JPT,EAS,true,false,55.0], [JPT,EAS,false,true,62.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,true,63.0], [JPT,EAS,true,false,60.0], [JPT,EAS,false,false,73.0], [JPT,EAS,true,true,65.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,false,62.0], [JPT,EAS,false,false,69.0], [JPT,EAS,false,false,70.0], [JPT,EAS,false,false,69.0], [JPT,EAS,true,false,71.0], [JPT,EAS,false,false,70.0], [JPT,EAS,true,false,61.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,true,58.0], [JPT,EAS,false,false,64.0], [JPT,EAS,false,false,62.0], [JPT,EAS,true,true,60.0], [JPT,EAS,true,true,63.0], [LWK,AFR,true,true,61.0], [LWK,AFR,false,false,60.0], [LWK,AFR,false,false,76.0], [LWK,AFR,true,false,58.0], [LWK,AFR,false,false,70.0], [JPT,EAS,false,true,68.0], [JPT,EAS,true,false,61.0], [JPT,EAS,false,false,72.0], [JPT,EAS,true,true,62.0], [JPT,EAS,false,false,69.0], [JPT,EAS,false,false,70.0], [JPT,EAS,false,false,74.0], [JPT,EAS,true,true,64.0], [JPT,EAS,true,true,62.0], [JPT,EAS,false,true,69.0], [JPT,EAS,false,true,71.0], [JPT,EAS,false,true,69.0], [YRI,AFR,true,true,63.0], [YRI,AFR,true,false,64.0], [YRI,AFR,false,false,71.0], [YRI,AFR,true,false,63.0], [YRI,AFR,true,false,60.0], [YRI,AFR,true,false,71.0], [YRI,AFR,true,false,66.0], [YRI,AFR,true,false,68.0], [YRI,AFR,false,true,63.0], [YRI,AFR,true,true,66.0], [YRI,AFR,false,true,71.0], [YRI,AFR,true,false,65.0], [YRI,AFR,true,true,64.0], [YRI,AFR,false,false,65.0], [YRI,AFR,true,false,58.0], [LWK,AFR,true,false,57.0], [LWK,AFR,true,false,68.0], [LWK,AFR,true,true,59.0], [LWK,AFR,true,true,66.0], [LWK,AFR,false,true,73.0], [LWK,AFR,false,false,76.0], [LWK,AFR,true,false,60.0], [LWK,AFR,false,false,73.0], [LWK,AFR,false,false,70.0], [LWK,AFR,false,false,73.0], [LWK,AFR,true,true,62.0], [LWK,AFR,true,true,67.0], [LWK,AFR,true,true,60.0], [LWK,AFR,false,false,70.0], [LWK,AFR,true,false,68.0], [LWK,AFR,true,false,62.0], [LWK,AFR,false,true,69.0], [LWK,AFR,true,false,64.0], [LWK,AFR,false,true,69.0], [LWK,AFR,true,true,58.0], [LWK,AFR,true,true,67.0], [LWK,AFR,true,false,62.0], [LWK,AFR,true,true,65.0], [ASW,AFR,true,true,60.0], [MXL,AMR,false,true,70.0], [MXL,AMR,true,true,69.0], [MXL,AMR,true,true,68.0], [ASW,AFR,false,true,69.0], [ASW,AFR,true,true,63.0], [ASW,AFR,false,false,66.0], [MXL,AMR,true,true,63.0], [MXL,AMR,false,false,72.0], [MXL,AMR,true,true,61.0], [MXL,AMR,true,false,67.0], [MXL,AMR,true,false,60.0], [MXL,AMR,false,true,69.0], [MXL,AMR,true,true,65.0], [MXL,AMR,true,false,72.0], [MXL,AMR,true,false,63.0], [MXL,AMR,true,false,66.0], [MXL,AMR,false,false,69.0], [MXL,AMR,true,false,58.0], [MXL,AMR,true,false,64.0], [MXL,AMR,true,true,63.0], [ASW,AFR,true,true,70.0], [ASW,AFR,false,false,72.0], [ASW,AFR,true,true,59.0], [ASW,AFR,true,false,66.0], [ASW,AFR,true,true,63.0], [ASW,AFR,false,false,69.0], [ASW,AFR,false,true,74.0], [ASW,AFR,true,false,62.0], [ASW,AFR,false,true,74.0], [ASW,AFR,false,true,71.0], [ASW,AFR,true,true,65.0], [ASW,AFR,true,false,66.0], [ASW,AFR,false,false,69.0], [ASW,AFR,false,true,74.0], [ASW,AFR,true,true,59.0], [TSI,EUR,true,true,63.0], [TSI,EUR,true,false,68.0], [TSI,EUR,false,true,69.0], [TSI,EUR,false,false,72.0], [TSI,EUR,true,false,71.0], [TSI,EUR,true,true,62.0], [TSI,EUR,false,false,73.0], [TSI,EUR,false,false,69.0], [TSI,EUR,true,true,62.0], [TSI,EUR,false,true,73.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,78.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,73.0], [TSI,EUR,true,false,66.0], [TSI,EUR,true,true,70.0], [TSI,EUR,true,true,68.0], [TSI,EUR,false,false,72.0], [TSI,EUR,false,false,74.0], [TSI,EUR,true,true,66.0], [TSI,EUR,true,true,65.0], [TSI,EUR,false,true,66.0], [TSI,EUR,true,true,70.0], [TSI,EUR,false,true,74.0], [TSI,EUR,false,false,73.0], [TSI,EUR,false,false,78.0], [TSI,EUR,true,true,69.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,74.0], [TSI,EUR,true,true,70.0], [TSI,EUR,true,true,63.0], [GIH,SAS,false,true,77.0], [GIH,SAS,true,true,65.0], [GIH,SAS,true,true,67.0], [GIH,SAS,false,true,72.0], [GIH,SAS,false,false,70.0], [GIH,SAS,true,false,70.0], [GIH,SAS,true,false,62.0], [GIH,SAS,false,true,73.0], [GIH,SAS,false,true,73.0], [GIH,SAS,true,true,69.0], [GIH,SAS,true,true,68.0], [GIH,SAS,true,false,68.0], [GIH,SAS,true,true,66.0], [GIH,SAS,true,false,71.0], [GIH,SAS,false,true,63.0], [GIH,SAS,false,false,67.0], [GIH,SAS,true,true,64.0], [GIH,SAS,true,false,62.0], [GIH,SAS,false,true,74.0], [GIH,SAS,false,false,68.0], [GIH,SAS,false,true,79.0], [GIH,SAS,false,true,77.0], [GIH,SAS,false,true,66.0], [GIH,SAS,true,true,68.0], [GIH,SAS,false,true,69.0], [GIH,SAS,true,false,68.0], [GIH,SAS,false,true,71.0], [GIH,SAS,false,true,76.0], [GIH,SAS,false,true,69.0], [GIH,SAS,true,false,67.0]), sampleIdsAndAnnotations=ArrayBuffer((HG00096,[GBR,EUR,false,false,77.0]), (HG00100,[GBR,EUR,true,false,59.0]), (HG00105,[GBR,EUR,false,false,77.0]), (HG00114,[GBR,EUR,false,true,72.0]), (HG00115,[GBR,EUR,false,true,71.0]), (HG00116,[GBR,EUR,false,false,71.0]), (HG00119,[GBR,EUR,false,true,70.0]), (HG00120,[GBR,EUR,true,true,68.0]), (HG00128,[GBR,EUR,true,true,67.0]), (HG00131,[GBR,EUR,false,false,72.0]), (HG00138,[GBR,EUR,false,false,74.0]), (HG00140,[GBR,EUR,false,false,78.0]), (HG00141,[GBR,EUR,false,false,77.0]), (HG00150,[GBR,EUR,true,true,64.0]), (HG00151,[GBR,EUR,false,false,69.0]), (HG00159,[GBR,EUR,false,false,64.0]), (HG00181,[FIN,EUR,false,true,62.0]), (HG00182,[FIN,EUR,false,false,72.0]), (HG00183,[FIN,EUR,false,false,69.0]), (HG00185,[FIN,EUR,false,true,70.0]), (HG00232,[GBR,EUR,true,true,69.0]), (HG00235,[GBR,EUR,true,true,73.0]), (HG00238,[GBR,EUR,true,true,66.0]), (HG00239,[GBR,EUR,true,true,64.0]), (HG00240,[GBR,EUR,true,false,65.0]), (HG00242,[GBR,EUR,false,false,70.0]), (HG00243,[GBR,EUR,false,true,63.0]), 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(HG03198,[ESN,AFR,true,false,64.0]), (HG03199,[ESN,AFR,false,true,69.0]), (HG03202,[ESN,AFR,false,false,71.0]), (HG03209,[MSL,AFR,false,false,70.0]), (HG03228,[PJL,SAS,false,true,71.0]), (HG03240,[GWD,AFR,false,true,71.0]), (HG03241,[GWD,AFR,true,false,66.0]), (HG03247,[GWD,AFR,true,false,67.0]), (HG03258,[GWD,AFR,false,false,71.0]), (HG03259,[GWD,AFR,true,false,62.0]), (HG03265,[ESN,AFR,false,false,65.0]), (HG03267,[ESN,AFR,true,true,65.0]), (HG03268,[ESN,AFR,false,false,74.0]), (HG03270,[ESN,AFR,true,true,69.0]), (HG03271,[ESN,AFR,false,false,69.0]), (HG03291,[ESN,AFR,true,false,64.0]), (HG03295,[ESN,AFR,false,false,65.0]), (HG03351,[ESN,AFR,true,false,68.0]), (HG03366,[ESN,AFR,true,false,62.0]), (HG03367,[ESN,AFR,false,false,60.0]), (HG03391,[MSL,AFR,false,false,67.0]), (HG03397,[MSL,AFR,false,false,63.0]), (HG03432,[MSL,AFR,false,false,62.0]), (HG03452,[MSL,AFR,true,false,61.0]), (HG03458,[MSL,AFR,true,false,65.0]), (HG03470,[MSL,AFR,true,false,67.0]), (HG03472,[MSL,AFR,false,true,74.0]), (HG03485,[MSL,AFR,true,true,59.0]), (HG03491,[PJL,SAS,true,true,62.0]), (HG03511,[ESN,AFR,true,false,65.0]), (HG03514,[ESN,AFR,true,false,56.0]), (HG03515,[ESN,AFR,false,true,69.0]), (HG03521,[ESN,AFR,false,false,68.0]), (HG03547,[MSL,AFR,false,false,75.0]), (HG03558,[MSL,AFR,true,true,69.0]), (HG03565,[MSL,AFR,false,true,70.0]), (HG03575,[MSL,AFR,true,false,65.0]), (HG03593,[BEB,SAS,false,false,68.0]), (HG03595,[BEB,SAS,true,true,65.0]), (HG03607,[BEB,SAS,true,false,66.0]), (HG03624,[PJL,SAS,false,true,65.0]), (HG03634,[PJL,SAS,true,false,60.0]), (HG03636,[PJL,SAS,false,true,70.0]), (HG03643,[STU,SAS,true,false,62.0]), (HG03646,[STU,SAS,false,false,64.0]), (HG03668,[PJL,SAS,true,false,62.0]), (HG03690,[STU,SAS,true,true,63.0]), (HG03703,[PJL,SAS,true,false,69.0]), (HG03716,[ITU,SAS,false,false,64.0]), (HG03720,[ITU,SAS,false,true,66.0]), (HG03740,[STU,SAS,false,true,65.0]), (HG03765,[PJL,SAS,true,false,60.0]), (HG03767,[PJL,SAS,false,false,73.0]), (HG03780,[ITU,SAS,true,false,62.0]), (HG03784,[ITU,SAS,true,true,64.0]), (HG03790,[ITU,SAS,false,false,72.0]), (HG03792,[ITU,SAS,false,true,69.0]), (HG03793,[BEB,SAS,true,false,70.0]), (HG03802,[BEB,SAS,true,true,63.0]), (HG03821,[BEB,SAS,false,false,62.0]), (HG03824,[BEB,SAS,false,false,67.0]), (HG03830,[BEB,SAS,false,true,76.0]), (HG03832,[BEB,SAS,true,false,65.0]), (HG03848,[STU,SAS,false,false,59.0]), (HG03849,[STU,SAS,true,false,71.0]), (HG03857,[STU,SAS,true,true,58.0]), (HG03863,[ITU,SAS,true,false,61.0]), (HG03871,[ITU,SAS,false,false,65.0]), (HG03874,[ITU,SAS,true,false,65.0]), (HG03875,[ITU,SAS,false,false,63.0]), (HG03884,[STU,SAS,true,true,61.0]), (HG03898,[STU,SAS,true,true,68.0]), (HG03899,[STU,SAS,false,true,70.0]), (HG03900,[STU,SAS,false,false,66.0]), (HG03914,[BEB,SAS,false,true,64.0]), (HG03916,[BEB,SAS,true,false,70.0]), (HG03917,[BEB,SAS,false,false,68.0]), (HG03931,[BEB,SAS,true,true,62.0]), (HG03934,[BEB,SAS,true,false,64.0]), (HG03943,[STU,SAS,false,true,67.0]), (HG03944,[STU,SAS,true,true,63.0]), (HG03945,[STU,SAS,true,false,69.0]), (HG03949,[STU,SAS,true,true,66.0]), (HG03955,[STU,SAS,true,true,64.0]), (HG03968,[ITU,SAS,true,true,61.0]), (HG03976,[ITU,SAS,false,false,63.0]), (HG03995,[STU,SAS,true,false,64.0]), (HG04006,[STU,SAS,false,true,69.0]), (HG04022,[ITU,SAS,false,true,69.0]), (HG04025,[ITU,SAS,true,false,62.0]), (HG04038,[STU,SAS,true,false,68.0]), (HG04054,[ITU,SAS,true,true,64.0]), (HG04059,[ITU,SAS,true,true,66.0]), (HG04061,[ITU,SAS,false,false,74.0]), (HG04062,[ITU,SAS,true,true,57.0]), (HG04076,[ITU,SAS,true,true,64.0]), (HG04094,[ITU,SAS,false,false,58.0]), (HG04107,[STU,SAS,false,true,67.0]), (HG04140,[BEB,SAS,false,false,67.0]), (HG04141,[BEB,SAS,true,true,65.0]), (HG04146,[BEB,SAS,false,false,59.0]), (HG04161,[BEB,SAS,false,false,69.0]), (HG04164,[BEB,SAS,false,true,69.0]), (HG04171,[BEB,SAS,true,true,70.0]), (HG04176,[BEB,SAS,false,false,71.0]), (HG04182,[BEB,SAS,false,false,69.0]), (HG04186,[BEB,SAS,true,true,70.0]), (HG04189,[BEB,SAS,true,false,66.0]), (HG04194,[BEB,SAS,false,false,66.0]), (HG04195,[BEB,SAS,true,false,65.0]), (HG04210,[STU,SAS,false,false,65.0]), (HG04219,[ITU,SAS,false,false,66.0]), (HG04225,[ITU,SAS,false,true,68.0]), (HG04229,[STU,SAS,false,false,70.0]), (HG04235,[ITU,SAS,false,false,65.0]), (NA06989,[CEU,EUR,true,true,61.0]), (NA07000,[CEU,EUR,true,false,60.0]), (NA07037,[CEU,EUR,true,true,60.0]), (NA07357,[CEU,EUR,false,true,71.0]), (NA10847,[CEU,EUR,true,true,66.0]), (NA10851,[CEU,EUR,false,false,74.0]), (NA11840,[CEU,EUR,true,true,67.0]), (NA11894,[CEU,EUR,true,false,61.0]), (NA11918,[CEU,EUR,true,false,61.0]), (NA11920,[CEU,EUR,true,false,65.0]), (NA11932,[CEU,EUR,false,true,62.0]), (NA11933,[CEU,EUR,true,true,68.0]), (NA11992,[CEU,EUR,false,true,74.0]), (NA11994,[CEU,EUR,false,false,74.0]), (NA12046,[CEU,EUR,true,false,70.0]), (NA12156,[CEU,EUR,true,false,64.0]), (NA12272,[CEU,EUR,false,true,73.0]), (NA12282,[CEU,EUR,false,false,61.0]), (NA12283,[CEU,EUR,true,true,65.0]), (NA12340,[CEU,EUR,false,false,66.0]), (NA12347,[CEU,EUR,false,false,70.0]), (NA12400,[CEU,EUR,true,true,63.0]), (NA12546,[CEU,EUR,false,true,57.0]), (NA12717,[CEU,EUR,true,true,73.0]), (NA12749,[CEU,EUR,true,false,63.0]), (NA12751,[CEU,EUR,true,true,64.0]), (NA12760,[CEU,EUR,false,false,63.0]), (NA12761,[CEU,EUR,true,true,64.0]), (NA12814,[CEU,EUR,false,true,65.0]), (NA12830,[CEU,EUR,true,true,64.0]), (NA12890,[CEU,EUR,true,true,64.0]), (NA18488,[YRI,AFR,true,false,66.0]), (NA18505,[YRI,AFR,true,false,61.0]), (NA18510,[YRI,AFR,false,true,67.0]), (NA18526,[CHB,EAS,true,false,63.0]), (NA18533,[CHB,EAS,true,false,62.0]), (NA18535,[CHB,EAS,true,true,64.0]), (NA18536,[CHB,EAS,false,true,67.0]), (NA18542,[CHB,EAS,true,false,55.0]), (NA18550,[CHB,EAS,true,true,66.0]), (NA18552,[CHB,EAS,true,true,61.0]), (NA18558,[CHB,EAS,false,true,73.0]), (NA18560,[CHB,EAS,true,false,61.0]), (NA18571,[CHB,EAS,true,true,67.0]), (NA18577,[CHB,EAS,true,true,59.0]), (NA18582,[CHB,EAS,true,false,60.0]), (NA18595,[CHB,EAS,true,true,57.0]), (NA18596,[CHB,EAS,true,true,65.0]), (NA18603,[CHB,EAS,false,true,65.0]), (NA18608,[CHB,EAS,false,false,73.0]), (NA18609,[CHB,EAS,false,true,73.0]), (NA18610,[CHB,EAS,true,false,68.0]), (NA18613,[CHB,EAS,false,false,73.0]), (NA18615,[CHB,EAS,true,false,64.0]), (NA18618,[CHB,EAS,true,false,64.0]), (NA18620,[CHB,EAS,false,true,72.0]), (NA18622,[CHB,EAS,false,true,69.0]), (NA18623,[CHB,EAS,false,true,66.0]), (NA18624,[CHB,EAS,false,false,72.0]), (NA18626,[CHB,EAS,true,false,59.0]), (NA18636,[CHB,EAS,false,false,73.0]), (NA18638,[CHB,EAS,false,true,73.0]), (NA18639,[CHB,EAS,false,true,74.0]), (NA18641,[CHB,EAS,true,false,67.0]), (NA18646,[CHB,EAS,true,true,66.0]), (NA18648,[CHB,EAS,false,true,65.0]), (NA18740,[CHB,EAS,false,true,65.0]), (NA18867,[YRI,AFR,true,false,65.0]), (NA18871,[YRI,AFR,false,false,72.0]), (NA18874,[YRI,AFR,false,true,64.0]), (NA18912,[YRI,AFR,true,false,67.0]), (NA18915,[YRI,AFR,false,true,69.0]), (NA18933,[YRI,AFR,true,true,64.0]), (NA18949,[JPT,EAS,true,true,64.0]), (NA18950,[JPT,EAS,true,true,68.0]), (NA18951,[JPT,EAS,true,false,55.0]), (NA18953,[JPT,EAS,false,true,62.0]), (NA18956,[JPT,EAS,true,false,64.0]), (NA18957,[JPT,EAS,true,true,63.0]), (NA18964,[JPT,EAS,true,false,60.0]), (NA18970,[JPT,EAS,false,false,73.0]), (NA18975,[JPT,EAS,true,true,65.0]), (NA18978,[JPT,EAS,true,false,64.0]), (NA18981,[JPT,EAS,true,false,62.0]), (NA18982,[JPT,EAS,false,false,69.0]), (NA18983,[JPT,EAS,false,false,70.0]), (NA18985,[JPT,EAS,false,false,69.0]), (NA18987,[JPT,EAS,true,false,71.0]), (NA18990,[JPT,EAS,false,false,70.0]), (NA18991,[JPT,EAS,true,false,61.0]), (NA18999,[JPT,EAS,true,false,64.0]), (NA19003,[JPT,EAS,true,true,58.0]), (NA19006,[JPT,EAS,false,false,64.0]), (NA19007,[JPT,EAS,false,false,62.0]), (NA19010,[JPT,EAS,true,true,60.0]), (NA19011,[JPT,EAS,true,true,63.0]), (NA19024,[LWK,AFR,true,true,61.0]), (NA19026,[LWK,AFR,false,false,60.0]), (NA19031,[LWK,AFR,false,false,76.0]), (NA19037,[LWK,AFR,true,false,58.0]), (NA19041,[LWK,AFR,false,false,70.0]), (NA19055,[JPT,EAS,false,true,68.0]), (NA19057,[JPT,EAS,true,false,61.0]), (NA19058,[JPT,EAS,false,false,72.0]), (NA19059,[JPT,EAS,true,true,62.0]), (NA19060,[JPT,EAS,false,false,69.0]), (NA19062,[JPT,EAS,false,false,70.0]), (NA19063,[JPT,EAS,false,false,74.0]), (NA19064,[JPT,EAS,true,true,64.0]), (NA19065,[JPT,EAS,true,true,62.0]), (NA19079,[JPT,EAS,false,true,69.0]), (NA19082,[JPT,EAS,false,true,71.0]), (NA19086,[JPT,EAS,false,true,69.0]), (NA19095,[YRI,AFR,true,true,63.0]), (NA19102,[YRI,AFR,true,false,64.0]), (NA19119,[YRI,AFR,false,false,71.0]), (NA19129,[YRI,AFR,true,false,63.0]), (NA19147,[YRI,AFR,true,false,60.0]), (NA19159,[YRI,AFR,true,false,71.0]), (NA19172,[YRI,AFR,true,false,66.0]), (NA19185,[YRI,AFR,true,false,68.0]), (NA19189,[YRI,AFR,false,true,63.0]), (NA19197,[YRI,AFR,true,true,66.0]), (NA19200,[YRI,AFR,false,true,71.0]), (NA19238,[YRI,AFR,true,false,65.0]), (NA19247,[YRI,AFR,true,true,64.0]), (NA19248,[YRI,AFR,false,false,65.0]), (NA19257,[YRI,AFR,true,false,58.0]), (NA19315,[LWK,AFR,true,false,57.0]), (NA19320,[LWK,AFR,true,false,68.0]), (NA19332,[LWK,AFR,true,true,59.0]), (NA19338,[LWK,AFR,true,true,66.0]), (NA19372,[LWK,AFR,false,true,73.0]), (NA19375,[LWK,AFR,false,false,76.0]), (NA19379,[LWK,AFR,true,false,60.0]), (NA19384,[LWK,AFR,false,false,73.0]), (NA19393,[LWK,AFR,false,false,70.0]), (NA19397,[LWK,AFR,false,false,73.0]), (NA19401,[LWK,AFR,true,true,62.0]), (NA19404,[LWK,AFR,true,true,67.0]), (NA19435,[LWK,AFR,true,true,60.0]), (NA19443,[LWK,AFR,false,false,70.0]), (NA19446,[LWK,AFR,true,false,68.0]), (NA19449,[LWK,AFR,true,false,62.0]), (NA19455,[LWK,AFR,false,true,69.0]), (NA19457,[LWK,AFR,true,false,64.0]), (NA19466,[LWK,AFR,false,true,69.0]), (NA19468,[LWK,AFR,true,true,58.0]), (NA19471,[LWK,AFR,true,true,67.0]), (NA19473,[LWK,AFR,true,false,62.0]), (NA19474,[LWK,AFR,true,true,65.0]), (NA19625,[ASW,AFR,true,true,60.0]), (NA19655,[MXL,AMR,false,true,70.0]), (NA19663,[MXL,AMR,true,true,69.0]), (NA19681,[MXL,AMR,true,true,68.0]), (NA19703,[ASW,AFR,false,true,69.0]), (NA19707,[ASW,AFR,true,true,63.0]), (NA19711,[ASW,AFR,false,false,66.0]), (NA19716,[MXL,AMR,true,true,63.0]), (NA19717,[MXL,AMR,false,false,72.0]), (NA19722,[MXL,AMR,true,true,61.0]), (NA19728,[MXL,AMR,true,false,67.0]), (NA19731,[MXL,AMR,true,false,60.0]), (NA19747,[MXL,AMR,false,true,69.0]), (NA19764,[MXL,AMR,true,true,65.0]), (NA19770,[MXL,AMR,true,false,...

Print schemas

Sample schema:

print(vds.saSignature)

Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double}

%md You can also print it in a more human-readable format:

print(vds.saSignature.schema.prettyJson)

{
  "type" : "struct",
  "fields" : [ {
    "name" : "Population",
    "type" : "string",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "SuperPopulation",
    "type" : "string",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "isFemale",
    "type" : "boolean",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "PurpleHair",
    "type" : "boolean",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "CaffeineConsumption",
    "type" : "double",
    "nullable" : true,
    "metadata" : { }
  } ]
}

Variant schema:

print(vds.vaSignature.schema.prettyJson)

{
  "type" : "struct",
  "fields" : [ {
    "name" : "rsid",
    "type" : "string",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "qual",
    "type" : "double",
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "filters",
    "type" : {
      "type" : "array",
      "elementType" : "string",
      "containsNull" : true
    },
    "nullable" : true,
    "metadata" : { }
  }, {
    "name" : "info",
    "type" : {
      "type" : "struct",
      "fields" : [ {
        "name" : "AC",
        "type" : {
          "type" : "array",
          "elementType" : "integer",
          "containsNull" : true
        },
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "AF",
        "type" : {
          "type" : "array",
          "elementType" : "double",
          "containsNull" : true
        },
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "AN",
        "type" : "integer",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "BaseQRankSum",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "ClippingRankSum",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "DP",
        "type" : "integer",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "DS",
        "type" : "boolean",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "FS",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "HaplotypeScore",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "InbreedingCoeff",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "MLEAC",
        "type" : {
          "type" : "array",
          "elementType" : "integer",
          "containsNull" : true
        },
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "MLEAF",
        "type" : {
          "type" : "array",
          "elementType" : "double",
          "containsNull" : true
        },
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "MQ",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "MQ0",
        "type" : "integer",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "MQRankSum",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "QD",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "ReadPosRankSum",
        "type" : "double",
        "nullable" : true,
        "metadata" : { }
      }, {
        "name" : "set",
        "type" : "string",
        "nullable" : true,
        "metadata" : { }
      } ]
    },
    "nullable" : true,
    "metadata" : { }
  } ]
}

Global schema

// vds.global_schema() in Hail's python API
print(vds.globalSignature)

Empty

We have not applied any global schema, so it is empty.

Count the number of samples

Total number of samples:

vds.nSamples

res20: Int = 710

Number of samples per population:

display(table.toDF(hc.sqlContext).groupBy("Population").count())

Explore the data

Print summary statistics:

print(vds.summarize())

SummaryResult(710,10961,Some(0.9881098285727502),Set(X, 12, 8, 19, 4, 15, 11, 9, 22, 13, 16, 5, 10, 21, 6, 1, 17, 14, 20, 2, 18, 7, 3),0,10961,0,0,0,0,0,2)

The above output shows:

• 710 - samples
• 10961 - variants
• 0.988 - successfully called genotypes.
• 23 - chromosomes
• 0 - multiallelic variants
• 10961 - SNPs
• 0 - MNP alternate alleles
• 0 - insertions
• 0 - deletions
• 0 - complex alternate alleles
• 0 - Number of star (upstream deletion)
• 2 - Highest number of alleles at any variant.

All these annotation variables can be called separately with a few extra steps described below:

Save the summarize output as a separate object:

val sumVDS = vds.summarize()

sumVDS: is.hail.utils.SummaryResult = SummaryResult(710,10961,Some(0.9881098285727502),Set(X, 12, 8, 19, 4, 15, 11, 9, 22, 13, 16, 5, 10, 21, 6, 1, 17, 14, 20, 2, 18, 7, 3),0,10961,0,0,0,0,0,2)

Now, place a dot after the summarize object and press TAB. You will be displayed all available variable. Select the variable of interest:

// sumVDS.       // remove the two back slashes "//" in front of the command, place the cursor after the dot and press TAB to see avaliable options.

Filter genotypes

Let's filter genotypes based on genotype quality (GQ) and read coverage (DP).

Here g is genotype, v is variant, s is sample, and annotations are accessible via va, sa, and global.

Genotype quality is measured with a Phred quality score. You can read more about it in the next cell.

Plot the genotype quality scores

Make a dataframe for genotypes:

val gtDF = vds.genotypeKT().flatten.toDF(hc.sqlContext)
display(gtDF)

Now extract the scores for genotype depth (g.dp) and genotype quality (g.gq) from the last column (g) with SQL.

There are many genotypes and using all of them make plotting computationally difficult. So, we will subset the score by randomly selecting 1% and limiting the number of rows to 3000. This should be enough to obtain general distributions and define cut-offs.

gtDF.createOrReplaceTempView("genotypes") 
val gtDFdpqc = spark.sql("SELECT g.dp as DEPTH, g.gq as GenQuality from genotypes WHERE g.dp IS NOT NULL AND g.gq IS NOT NULL and RAND() <= .01 LIMIT 3000")
display(gtDFdpqc)

Truncated to 30 rows

Using Databricks built-in display option, make plots for the extracted scores:

display(gtDFdpqc)

Truncated to 30 rows

From the plots, we can define that genotypes with genotype quality less than 10 and coverage less than 2 can be removed:

var vdsGfilter = vds.filterGenotypes("g.dp >= 2 && g.gq >= 10")

vdsGfilter: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}},Empty,Genotype,true,false,false), rdd=OrderedRDD[88] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00114, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00150, HG00151, HG00159, HG00181, HG00182, HG00183, HG00185, HG00232, HG00235, HG00238, HG00239, HG00240, HG00242, HG00243, HG00244, HG00245, HG00246, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00269, HG00271, HG00272, HG00273, HG00280, HG00290, HG00304, HG00311, HG00321, HG00323, HG00324, HG00326, HG00332, HG00334, HG00343, HG00356, HG00362, HG00367, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00565, HG00566, HG00583, HG00584, HG00592, HG00593, HG00598, HG00620, HG00635, HG00650, HG00654, HG00675, HG00701, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG00879, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01168, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01437, HG01438, HG01464, HG01474, HG01479, HG01488, HG01501, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01672, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01989, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03022, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12272, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18609, NA18610, NA18613, NA18615, NA18618, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18871, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19082, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19468, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19711, NA19716, NA19717, NA19722, NA19728, NA19731, NA19747, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20851, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21123, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=710, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0], [GBR,EUR,true,false,59.0], [GBR,EUR,false,false,77.0], [GBR,EUR,false,true,72.0], [GBR,EUR,false,true,71.0], [GBR,EUR,false,false,71.0], [GBR,EUR,false,true,70.0], [GBR,EUR,true,true,68.0], [GBR,EUR,true,true,67.0], [GBR,EUR,false,false,72.0], [GBR,EUR,false,false,74.0], [GBR,EUR,false,false,78.0], [GBR,EUR,false,false,77.0], [GBR,EUR,true,true,64.0], [GBR,EUR,false,false,69.0], [GBR,EUR,false,false,64.0], [FIN,EUR,false,true,62.0], [FIN,EUR,false,false,72.0], [FIN,EUR,false,false,69.0], [FIN,EUR,false,true,70.0], [GBR,EUR,true,true,69.0], [GBR,EUR,true,true,73.0], [GBR,EUR,true,true,66.0], [GBR,EUR,true,true,64.0], [GBR,EUR,true,false,65.0], [GBR,EUR,false,false,70.0], [GBR,EUR,false,true,63.0], [GBR,EUR,false,false,73.0], [GBR,EUR,true,false,72.0], [GBR,EUR,false,false,72.0], [GBR,EUR,true,false,67.0], [GBR,EUR,true,false,64.0], [GBR,EUR,true,true,68.0], [GBR,EUR,true,true,64.0], [GBR,EUR,true,true,66.0], [GBR,EUR,false,true,73.0], [FIN,EUR,true,true,67.0], [FIN,EUR,false,false,73.0], [FIN,EUR,true,true,71.0], [FIN,EUR,false,true,67.0], [FIN,EUR,false,false,70.0], [FIN,EUR,false,false,71.0], [FIN,EUR,true,true,65.0], [FIN,EUR,false,true,71.0], [FIN,EUR,false,false,79.0], [FIN,EUR,true,false,58.0], [FIN,EUR,true,true,61.0], [FIN,EUR,true,false,64.0], [FIN,EUR,true,true,60.0], [FIN,EUR,true,false,68.0], [FIN,EUR,true,true,64.0], [FIN,EUR,true,true,74.0], [FIN,EUR,true,true,63.0], [FIN,EUR,true,false,66.0], [FIN,EUR,false,true,71.0], [CHS,EAS,true,false,64.0], [CHS,EAS,true,true,68.0], [CHS,EAS,true,true,70.0], [CHS,EAS,true,true,66.0], [CHS,EAS,true,false,64.0], [CHS,EAS,false,true,71.0], [CHS,EAS,true,false,64.0], [CHS,EAS,false,true,75.0], [CHS,EAS,false,false,79.0], [CHS,EAS,false,true,77.0], [CHS,EAS,true,true,69.0], [CHS,EAS,false,false,69.0], [CHS,EAS,true,true,65.0], [CHS,EAS,false,true,76.0], [CHS,EAS,true,true,62.0], [CHS,EAS,false,true,65.0], [CHS,EAS,true,true,69.0], [CHS,EAS,false,false,71.0], [CHS,EAS,true,false,65.0], [CHS,EAS,false,true,66.0], [CHS,EAS,true,false,61.0], [CHS,EAS,true,false,69.0], [CHS,EAS,false,true,70.0], [CHS,EAS,true,true,66.0], [CHS,EAS,true,false,66.0], [CHS,EAS,false,true,67.0], [CHS,EAS,true,false,70.0], [CHS,EAS,false,true,70.0], [CHS,EAS,true,true,65.0], [CHS,EAS,false,true,70.0], [PUR,AMR,true,true,65.0], [CDX,EAS,true,true,64.0], [CDX,EAS,true,true,63.0], [CDX,EAS,true,false,65.0], [CDX,EAS,true,true,74.0], [PUR,AMR,false,false,74.0], [PUR,AMR,false,false,65.0], [PUR,AMR,true,true,66.0], [PUR,AMR,false,false,68.0], [PUR,AMR,true,false,69.0], [PUR,AMR,true,false,62.0], [PUR,AMR,false,false,73.0], [PUR,AMR,false,false,71.0], [PUR,AMR,true,true,61.0], [PUR,AMR,false,false,74.0], [CLM,AMR,false,true,61.0], [CLM,AMR,true,true,65.0], [CLM,AMR,false,false,73.0], [CLM,AMR,true,false,66.0], [CLM,AMR,false,false,69.0], [PUR,AMR,true,false,60.0], [PUR,AMR,false,true,80.0], [PUR,AMR,true,true,64.0], [PUR,AMR,true,true,67.0], [PUR,AMR,false,false,70.0], [PUR,AMR,true,false,72.0], [PUR,AMR,true,true,65.0], [PUR,AMR,true,true,60.0], [CLM,AMR,true,true,66.0], [CLM,AMR,false,true,71.0], [CLM,AMR,false,false,67.0], [CLM,AMR,true,true,63.0], [CLM,AMR,true,false,68.0], [PUR,AMR,false,false,70.0], [PUR,AMR,false,false,72.0], [PUR,AMR,true,false,65.0], [GBR,EUR,false,false,76.0], [CLM,AMR,false,true,75.0], [CLM,AMR,false,true,75.0], [CLM,AMR,false,false,72.0], [CLM,AMR,true,true,63.0], [CLM,AMR,false,true,69.0], [CLM,AMR,true,false,66.0], [CLM,AMR,true,false,62.0], [CLM,AMR,true,false,67.0], [PUR,AMR,false,false,76.0], [PUR,AMR,false,false,69.0], [CLM,AMR,false,false,71.0], [CLM,AMR,true,false,72.0], [CLM,AMR,false,false,67.0], [CLM,AMR,true,false,63.0], [CLM,AMR,false,true,72.0], [CLM,AMR,false,true,73.0], [IBS,EUR,true,false,72.0], [IBS,EUR,false,true,72.0], [IBS,EUR,false,false,69.0], [IBS,EUR,true,false,63.0], [IBS,EUR,true,true,58.0], [IBS,EUR,true,true,64.0], [CLM,AMR,false,false,73.0], [PEL,AMR,false,true,72.0], [PJL,SAS,false,true,66.0], [KHV,EAS,true,true,62.0], [IBS,EUR,false,false,59.0], [IBS,EUR,false,false,73.0], [IBS,EUR,false,true,68.0], [IBS,EUR,true,false,62.0], [IBS,EUR,false,false,68.0], [IBS,EUR,false,true,70.0], [IBS,EUR,false,true,77.0], [IBS,EUR,false,true,62.0], [IBS,EUR,false,false,69.0], [IBS,EUR,false,false,72.0], [IBS,EUR,false,true,72.0], [IBS,EUR,true,false,63.0], [IBS,EUR,false,true,66.0], [IBS,EUR,false,true,71.0], [IBS,EUR,true,false,67.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,true,67.0], [CDX,EAS,true,true,64.0], [CDX,EAS,true,false,61.0], [CDX,EAS,true,false,64.0], [CDX,EAS,false,false,69.0], [CDX,EAS,true,false,64.0], [CDX,EAS,true,false,62.0], [CDX,EAS,false,true,71.0], [KHV,EAS,false,false,74.0], [KHV,EAS,true,false,68.0], [KHV,EAS,false,false,75.0], [KHV,EAS,false,false,68.0], [KHV,EAS,false,false,71.0], [KHV,EAS,true,true,66.0], [KHV,EAS,false,true,65.0], [ACB,AFR,true,false,71.0], [PEL,AMR,false,false,66.0], [PEL,AMR,true,false,64.0], [ACB,AFR,false,false,67.0], [PEL,AMR,false,true,75.0], [PEL,AMR,false,true,75.0], [PEL,AMR,false,false,76.0], [PEL,AMR,true,false,69.0], [PEL,AMR,true,false,69.0], [PEL,AMR,false,true,74.0], [PEL,AMR,true,true,60.0], [PEL,AMR,false,false,70.0], [PEL,AMR,true,true,68.0], [PEL,AMR,false,false,71.0], [PEL,AMR,true,true,67.0], [PEL,AMR,false,false,80.0], [PEL,AMR,false,true,74.0], [ACB,AFR,true,false,61.0], [PEL,AMR,true,false,69.0], [PEL,AMR,false,false,68.0], [KHV,EAS,false,true,76.0], [KHV,EAS,true,true,64.0], [KHV,EAS,true,false,65.0], [KHV,EAS,false,true,68.0], [KHV,EAS,false,true,76.0], [KHV,EAS,true,true,66.0], [ACB,AFR,false,false,68.0], [KHV,EAS,true,true,67.0], [KHV,EAS,false,true,69.0], [KHV,EAS,true,true,64.0], [KHV,EAS,false,false,67.0], [KHV,EAS,true,true,67.0], [KHV,EAS,true,true,67.0], [PEL,AMR,true,true,68.0], [ACB,AFR,true,false,66.0], [PEL,AMR,true,false,66.0], [PEL,AMR,false,true,64.0], [ACB,AFR,true,true,63.0], [ACB,AFR,true,true,65.0], [KHV,EAS,true,true,67.0], [KHV,EAS,true,false,69.0], [KHV,EAS,true,true,68.0], [KHV,EAS,true,true,63.0], [ACB,AFR,false,true,71.0], [PEL,AMR,false,false,69.0], [CDX,EAS,true,true,62.0], [CDX,EAS,true,false,67.0], [CDX,EAS,true,true,65.0], [IBS,EUR,true,true,62.0], [PEL,AMR,true,true,68.0], [ACB,AFR,false,true,71.0], [PEL,AMR,false,true,66.0], [PEL,AMR,false,true,73.0], [PEL,AMR,false,true,65.0], [PEL,AMR,false,true,67.0], [ACB,AFR,false,true,70.0], [ACB,AFR,true,true,67.0], [ACB,AFR,false,false,71.0], [PEL,AMR,true,true,68.0], [PEL,AMR,true,false,66.0], [PEL,AMR,false,true,61.0], [ACB,AFR,true,true,62.0], [ACB,AFR,true,true,61.0], [ACB,AFR,true,false,70.0], [ACB,AFR,true,true,62.0], [ACB,AFR,false,true,66.0], [ACB,AFR,true,false,66.0], [ACB,AFR,false,true,59.0], [CDX,EAS,false,false,62.0], [CDX,EAS,false,false,72.0], [CDX,EAS,false,true,71.0], [CDX,EAS,false,true,69.0], [CDX,EAS,false,true,74.0], [CDX,EAS,false,true,66.0], [CDX,EAS,false,true,70.0], [CDX,EAS,false,false,71.0], [CDX,EAS,false,false,71.0], [ACB,AFR,true,false,61.0], [ACB,AFR,false,false,72.0], [ACB,AFR,false,true,73.0], [ACB,AFR,true,true,68.0], [ACB,AFR,false,true,70.0], [ACB,AFR,false,true,72.0], [PJL,SAS,true,true,66.0], [ACB,AFR,true,false,63.0], [ACB,AFR,true,false,65.0], [KHV,EAS,false,false,66.0], [ACB,AFR,true,false,61.0], [ACB,AFR,false,false,70.0], [ACB,AFR,true,true,67.0], [ACB,AFR,false,false,70.0], [GWD,AFR,true,false,66.0], [GWD,AFR,true,false,67.0], [ACB,AFR,true,true,66.0], [ACB,AFR,true,true,57.0], [GWD,AFR,true,true,71.0], [GWD,AFR,true,true,68.0], [PJL,SAS,true,true,67.0], [GWD,AFR,false,false,72.0], [GWD,AFR,true,true,72.0], [GWD,AFR,false,true,73.0], [GWD,AFR,false,false,74.0], [PJL,SAS,true,false,66.0], [PJL,SAS,false,true,69.0], [PJL,SAS,true,true,67.0], [PJL,SAS,false,true,70.0], [PJL,SAS,false,false,72.0], [GWD,AFR,false,true,66.0], [GWD,AFR,true,false,68.0], [GWD,AFR,false,true,68.0], [GWD,AFR,true,false,66.0], [PJL,SAS,true,false,69.0], [PJL,SAS,false,false,72.0], [PJL,SAS,true,false,70.0], [PJL,SAS,false,false,69.0], [GWD,AFR,true,false,72.0], [PJL,SAS,false,false,71.0], [PJL,SAS,true,true,64.0], [PJL,SAS,true,false,73.0], [GWD,AFR,true,true,64.0], [GWD,AFR,false,true,67.0], [GWD,AFR,true,false,69.0], [GWD,AFR,false,true,68.0], [PJL,SAS,false,false,73.0], [PJL,SAS,false,false,72.0], [PJL,SAS,true,true,62.0], [PJL,SAS,false,false,65.0], [GWD,AFR,false,false,70.0], [GWD,AFR,false,false,66.0], [GWD,AFR,true,true,65.0], [GWD,AFR,false,false,68.0], [GWD,AFR,true,true,66.0], [GWD,AFR,false,false,69.0], [GWD,AFR,true,false,64.0], [GWD,AFR,false,true,72.0], [GWD,AFR,false,true,64.0], [GWD,AFR,true,true,68.0], [GWD,AFR,true,false,67.0], [GWD,AFR,false,true,69.0], [GWD,AFR,false,true,73.0], [ESN,AFR,false,false,67.0], [ESN,AFR,false,true,70.0], [ESN,AFR,false,false,64.0], [ESN,AFR,false,true,66.0], [ESN,AFR,true,true,66.0], [ESN,AFR,true,true,63.0], [ESN,AFR,false,false,63.0], [GWD,AFR,true,false,64.0], [BEB,SAS,false,false,69.0], [PJL,SAS,false,false,68.0], [PJL,SAS,true,true,66.0], [GWD,AFR,false,true,65.0], [GWD,AFR,true,true,67.0], [GWD,AFR,true,false,61.0], [MSL,AFR,false,false,71.0], [MSL,AFR,false,true,71.0], [MSL,AFR,false,false,68.0], [MSL,AFR,true,true,60.0], [MSL,AFR,true,true,61.0], [ESN,AFR,false,true,65.0], [ESN,AFR,true,true,66.0], [ESN,AFR,false,false,71.0], [ESN,AFR,true,true,60.0], [ESN,AFR,false,false,66.0], [ESN,AFR,false,true,64.0], [ESN,AFR,true,true,65.0], [ESN,AFR,false,true,74.0], [ESN,AFR,true,false,64.0], [ESN,AFR,false,true,69.0], [ESN,AFR,false,false,71.0], [MSL,AFR,false,false,70.0], [PJL,SAS,false,true,71.0], [GWD,AFR,false,true,71.0], [GWD,AFR,true,false,66.0], [GWD,AFR,true,false,67.0], [GWD,AFR,false,false,71.0], [GWD,AFR,true,false,62.0], [ESN,AFR,false,false,65.0], [ESN,AFR,true,true,65.0], [ESN,AFR,false,false,74.0], [ESN,AFR,true,true,69.0], [ESN,AFR,false,false,69.0], [ESN,AFR,true,false,64.0], [ESN,AFR,false,false,65.0], [ESN,AFR,true,false,68.0], [ESN,AFR,true,false,62.0], [ESN,AFR,false,false,60.0], [MSL,AFR,false,false,67.0], [MSL,AFR,false,false,63.0], [MSL,AFR,false,false,62.0], [MSL,AFR,true,false,61.0], [MSL,AFR,true,false,65.0], [MSL,AFR,true,false,67.0], [MSL,AFR,false,true,74.0], [MSL,AFR,true,true,59.0], [PJL,SAS,true,true,62.0], [ESN,AFR,true,false,65.0], [ESN,AFR,true,false,56.0], [ESN,AFR,false,true,69.0], [ESN,AFR,false,false,68.0], [MSL,AFR,false,false,75.0], [MSL,AFR,true,true,69.0], [MSL,AFR,false,true,70.0], [MSL,AFR,true,false,65.0], [BEB,SAS,false,false,68.0], [BEB,SAS,true,true,65.0], [BEB,SAS,true,false,66.0], [PJL,SAS,false,true,65.0], [PJL,SAS,true,false,60.0], [PJL,SAS,false,true,70.0], [STU,SAS,true,false,62.0], [STU,SAS,false,false,64.0], [PJL,SAS,true,false,62.0], [STU,SAS,true,true,63.0], [PJL,SAS,true,false,69.0], [ITU,SAS,false,false,64.0], [ITU,SAS,false,true,66.0], [STU,SAS,false,true,65.0], [PJL,SAS,true,false,60.0], [PJL,SAS,false,false,73.0], [ITU,SAS,true,false,62.0], [ITU,SAS,true,true,64.0], [ITU,SAS,false,false,72.0], [ITU,SAS,false,true,69.0], [BEB,SAS,true,false,70.0], [BEB,SAS,true,true,63.0], [BEB,SAS,false,false,62.0], [BEB,SAS,false,false,67.0], [BEB,SAS,false,true,76.0], [BEB,SAS,true,false,65.0], [STU,SAS,false,false,59.0], [STU,SAS,true,false,71.0], [STU,SAS,true,true,58.0], [ITU,SAS,true,false,61.0], [ITU,SAS,false,false,65.0], [ITU,SAS,true,false,65.0], [ITU,SAS,false,false,63.0], [STU,SAS,true,true,61.0], [STU,SAS,true,true,68.0], [STU,SAS,false,true,70.0], [STU,SAS,false,false,66.0], [BEB,SAS,false,true,64.0], [BEB,SAS,true,false,70.0], [BEB,SAS,false,false,68.0], [BEB,SAS,true,true,62.0], [BEB,SAS,true,false,64.0], [STU,SAS,false,true,67.0], [STU,SAS,true,true,63.0], [STU,SAS,true,false,69.0], [STU,SAS,true,true,66.0], [STU,SAS,true,true,64.0], [ITU,SAS,true,true,61.0], [ITU,SAS,false,false,63.0], [STU,SAS,true,false,64.0], [STU,SAS,false,true,69.0], [ITU,SAS,false,true,69.0], [ITU,SAS,true,false,62.0], [STU,SAS,true,false,68.0], [ITU,SAS,true,true,64.0], [ITU,SAS,true,true,66.0], [ITU,SAS,false,false,74.0], [ITU,SAS,true,true,57.0], [ITU,SAS,true,true,64.0], [ITU,SAS,false,false,58.0], [STU,SAS,false,true,67.0], [BEB,SAS,false,false,67.0], [BEB,SAS,true,true,65.0], [BEB,SAS,false,false,59.0], [BEB,SAS,false,false,69.0], [BEB,SAS,false,true,69.0], [BEB,SAS,true,true,70.0], [BEB,SAS,false,false,71.0], [BEB,SAS,false,false,69.0], [BEB,SAS,true,true,70.0], [BEB,SAS,true,false,66.0], [BEB,SAS,false,false,66.0], [BEB,SAS,true,false,65.0], [STU,SAS,false,false,65.0], [ITU,SAS,false,false,66.0], [ITU,SAS,false,true,68.0], [STU,SAS,false,false,70.0], [ITU,SAS,false,false,65.0], [CEU,EUR,true,true,61.0], [CEU,EUR,true,false,60.0], [CEU,EUR,true,true,60.0], [CEU,EUR,false,true,71.0], [CEU,EUR,true,true,66.0], [CEU,EUR,false,false,74.0], [CEU,EUR,true,true,67.0], [CEU,EUR,true,false,61.0], [CEU,EUR,true,false,61.0], [CEU,EUR,true,false,65.0], [CEU,EUR,false,true,62.0], [CEU,EUR,true,true,68.0], [CEU,EUR,false,true,74.0], [CEU,EUR,false,false,74.0], [CEU,EUR,true,false,70.0], [CEU,EUR,true,false,64.0], [CEU,EUR,false,true,73.0], [CEU,EUR,false,false,61.0], [CEU,EUR,true,true,65.0], [CEU,EUR,false,false,66.0], [CEU,EUR,false,false,70.0], [CEU,EUR,true,true,63.0], [CEU,EUR,false,true,57.0], [CEU,EUR,true,true,73.0], [CEU,EUR,true,false,63.0], [CEU,EUR,true,true,64.0], [CEU,EUR,false,false,63.0], [CEU,EUR,true,true,64.0], [CEU,EUR,false,true,65.0], [CEU,EUR,true,true,64.0], [CEU,EUR,true,true,64.0], [YRI,AFR,true,false,66.0], [YRI,AFR,true,false,61.0], [YRI,AFR,false,true,67.0], [CHB,EAS,true,false,63.0], [CHB,EAS,true,false,62.0], [CHB,EAS,true,true,64.0], [CHB,EAS,false,true,67.0], [CHB,EAS,true,false,55.0], [CHB,EAS,true,true,66.0], [CHB,EAS,true,true,61.0], [CHB,EAS,false,true,73.0], [CHB,EAS,true,false,61.0], [CHB,EAS,true,true,67.0], [CHB,EAS,true,true,59.0], [CHB,EAS,true,false,60.0], [CHB,EAS,true,true,57.0], [CHB,EAS,true,true,65.0], [CHB,EAS,false,true,65.0], [CHB,EAS,false,false,73.0], [CHB,EAS,false,true,73.0], [CHB,EAS,true,false,68.0], [CHB,EAS,false,false,73.0], [CHB,EAS,true,false,64.0], [CHB,EAS,true,false,64.0], [CHB,EAS,false,true,72.0], [CHB,EAS,false,true,69.0], [CHB,EAS,false,true,66.0], [CHB,EAS,false,false,72.0], [CHB,EAS,true,false,59.0], [CHB,EAS,false,false,73.0], [CHB,EAS,false,true,73.0], [CHB,EAS,false,true,74.0], [CHB,EAS,true,false,67.0], [CHB,EAS,true,true,66.0], [CHB,EAS,false,true,65.0], [CHB,EAS,false,true,65.0], [YRI,AFR,true,false,65.0], [YRI,AFR,false,false,72.0], [YRI,AFR,false,true,64.0], [YRI,AFR,true,false,67.0], [YRI,AFR,false,true,69.0], [YRI,AFR,true,true,64.0], [JPT,EAS,true,true,64.0], [JPT,EAS,true,true,68.0], [JPT,EAS,true,false,55.0], [JPT,EAS,false,true,62.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,true,63.0], [JPT,EAS,true,false,60.0], [JPT,EAS,false,false,73.0], [JPT,EAS,true,true,65.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,false,62.0], [JPT,EAS,false,false,69.0], [JPT,EAS,false,false,70.0], [JPT,EAS,false,false,69.0], [JPT,EAS,true,false,71.0], [JPT,EAS,false,false,70.0], [JPT,EAS,true,false,61.0], [JPT,EAS,true,false,64.0], [JPT,EAS,true,true,58.0], [JPT,EAS,false,false,64.0], [JPT,EAS,false,false,62.0], [JPT,EAS,true,true,60.0], [JPT,EAS,true,true,63.0], [LWK,AFR,true,true,61.0], [LWK,AFR,false,false,60.0], [LWK,AFR,false,false,76.0], [LWK,AFR,true,false,58.0], [LWK,AFR,false,false,70.0], [JPT,EAS,false,true,68.0], [JPT,EAS,true,false,61.0], [JPT,EAS,false,false,72.0], [JPT,EAS,true,true,62.0], [JPT,EAS,false,false,69.0], [JPT,EAS,false,false,70.0], [JPT,EAS,false,false,74.0], [JPT,EAS,true,true,64.0], [JPT,EAS,true,true,62.0], [JPT,EAS,false,true,69.0], [JPT,EAS,false,true,71.0], [JPT,EAS,false,true,69.0], [YRI,AFR,true,true,63.0], [YRI,AFR,true,false,64.0], [YRI,AFR,false,false,71.0], [YRI,AFR,true,false,63.0], [YRI,AFR,true,false,60.0], [YRI,AFR,true,false,71.0], [YRI,AFR,true,false,66.0], [YRI,AFR,true,false,68.0], [YRI,AFR,false,true,63.0], [YRI,AFR,true,true,66.0], [YRI,AFR,false,true,71.0], [YRI,AFR,true,false,65.0], [YRI,AFR,true,true,64.0], [YRI,AFR,false,false,65.0], [YRI,AFR,true,false,58.0], [LWK,AFR,true,false,57.0], [LWK,AFR,true,false,68.0], [LWK,AFR,true,true,59.0], [LWK,AFR,true,true,66.0], [LWK,AFR,false,true,73.0], [LWK,AFR,false,false,76.0], [LWK,AFR,true,false,60.0], [LWK,AFR,false,false,73.0], [LWK,AFR,false,false,70.0], [LWK,AFR,false,false,73.0], [LWK,AFR,true,true,62.0], [LWK,AFR,true,true,67.0], [LWK,AFR,true,true,60.0], [LWK,AFR,false,false,70.0], [LWK,AFR,true,false,68.0], [LWK,AFR,true,false,62.0], [LWK,AFR,false,true,69.0], [LWK,AFR,true,false,64.0], [LWK,AFR,false,true,69.0], [LWK,AFR,true,true,58.0], [LWK,AFR,true,true,67.0], [LWK,AFR,true,false,62.0], [LWK,AFR,true,true,65.0], [ASW,AFR,true,true,60.0], [MXL,AMR,false,true,70.0], [MXL,AMR,true,true,69.0], [MXL,AMR,true,true,68.0], [ASW,AFR,false,true,69.0], [ASW,AFR,true,true,63.0], [ASW,AFR,false,false,66.0], [MXL,AMR,true,true,63.0], [MXL,AMR,false,false,72.0], [MXL,AMR,true,true,61.0], [MXL,AMR,true,false,67.0], [MXL,AMR,true,false,60.0], [MXL,AMR,false,true,69.0], [MXL,AMR,true,true,65.0], [MXL,AMR,true,false,72.0], [MXL,AMR,true,false,63.0], [MXL,AMR,true,false,66.0], [MXL,AMR,false,false,69.0], [MXL,AMR,true,false,58.0], [MXL,AMR,true,false,64.0], [MXL,AMR,true,true,63.0], [ASW,AFR,true,true,70.0], [ASW,AFR,false,false,72.0], [ASW,AFR,true,true,59.0], [ASW,AFR,true,false,66.0], [ASW,AFR,true,true,63.0], [ASW,AFR,false,false,69.0], [ASW,AFR,false,true,74.0], [ASW,AFR,true,false,62.0], [ASW,AFR,false,true,74.0], [ASW,AFR,false,true,71.0], [ASW,AFR,true,true,65.0], [ASW,AFR,true,false,66.0], [ASW,AFR,false,false,69.0], [ASW,AFR,false,true,74.0], [ASW,AFR,true,true,59.0], [TSI,EUR,true,true,63.0], [TSI,EUR,true,false,68.0], [TSI,EUR,false,true,69.0], [TSI,EUR,false,false,72.0], [TSI,EUR,true,false,71.0], [TSI,EUR,true,true,62.0], [TSI,EUR,false,false,73.0], [TSI,EUR,false,false,69.0], [TSI,EUR,true,true,62.0], [TSI,EUR,false,true,73.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,78.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,73.0], [TSI,EUR,true,false,66.0], [TSI,EUR,true,true,70.0], [TSI,EUR,true,true,68.0], [TSI,EUR,false,false,72.0], [TSI,EUR,false,false,74.0], [TSI,EUR,true,true,66.0], [TSI,EUR,true,true,65.0], [TSI,EUR,false,true,66.0], [TSI,EUR,true,true,70.0], [TSI,EUR,false,true,74.0], [TSI,EUR,false,false,73.0], [TSI,EUR,false,false,78.0], [TSI,EUR,true,true,69.0], [TSI,EUR,false,false,70.0], [TSI,EUR,false,false,74.0], [TSI,EUR,true,true,70.0], [TSI,EUR,true,true,63.0], [GIH,SAS,false,true,77.0], [GIH,SAS,true,true,65.0], [GIH,SAS,true,true,67.0], [GIH,SAS,false,true,72.0], [GIH,SAS,false,false,70.0], [GIH,SAS,true,false,70.0], [GIH,SAS,true,false,62.0], [GIH,SAS,false,true,73.0], [GIH,SAS,false,true,73.0], [GIH,SAS,true,true,69.0], [GIH,SAS,true,true,68.0], [GIH,SAS,true,false,68.0], [GIH,SAS,true,true,66.0], [GIH,SAS,true,false,71.0], [GIH,SAS,false,true,63.0], [GIH,SAS,false,false,67.0], [GIH,SAS,true,true,64.0], [GIH,SAS,true,false,62.0], [GIH,SAS,false,true,74.0], [GIH,SAS,false,false,68.0], [GIH,SAS,false,true,79.0], [GIH,SAS,false,true,77.0], [GIH,SAS,false,true,66.0], [GIH,SAS,true,true,68.0], [GIH,SAS,false,true,69.0], [GIH,SAS,true,false,68.0], [GIH,SAS,false,true,71.0], [GIH,SAS,false,true,76.0], [GIH,SAS,false,true,69.0], [GIH,SAS,true,false,67.0]), sampleIdsAndAnnotations=ArrayBuffer((HG00096,[GBR,EUR,false,false,77.0]), (HG00100,[GBR,EUR,true,false,59.0]), (HG00105,[GBR,EUR,false,false,77.0]), (HG00114,[GBR,EUR,false,true,72.0]), (HG00115,[GBR,EUR,false,true,71.0]), (HG00116,[GBR,EUR,false,false,71.0]), (HG00119,[GBR,EUR,false,true,70.0]), (HG00120,[GBR,EUR,true,true,68.0]), (HG00128,[GBR,EUR,true,true,67.0]), (HG00131,[GBR,EUR,false,false,72.0]), (HG00138,[GBR,EUR,false,false,74.0]), (HG00140,[GBR,EUR,false,false,78.0]), (HG00141,[GBR,EUR,false,false,77.0]), (HG00150,[GBR,EUR,true,true,64.0]), (HG00151,[GBR,EUR,false,false,69.0]), (HG00159,[GBR,EUR,false,false,64.0]), (HG00181,[FIN,EUR,false,true,62.0]), (HG00182,[FIN,EUR,false,false,72.0]), (HG00183,[FIN,EUR,false,false,69.0]), (HG00185,[FIN,EUR,false,true,70.0]), (HG00232,[GBR,EUR,true,true,69.0]), (HG00235,[GBR,EUR,true,true,73.0]), (HG00238,[GBR,EUR,true,true,66.0]), (HG00239,[GBR,EUR,true,true,64.0]), (HG00240,[GBR,EUR,true,false,65.0]), (HG00242,[GBR,EUR,false,false,70.0]), (HG00243,[GBR,EUR,false,true,63.0]), (HG00244,[GBR,EUR,false,false,73.0]), (HG00245,[GBR,EUR,true,false,72.0]), (HG00246,[GBR,EUR,false,false,72.0]), (HG00250,[GBR,EUR,true,false,67.0]), (HG00254,[GBR,EUR,true,false,64.0]), (HG00257,[GBR,EUR,true,true,68.0]), (HG00258,[GBR,EUR,true,true,64.0]), (HG00261,[GBR,EUR,true,true,66.0]), (HG00264,[GBR,EUR,false,true,73.0]), (HG00269,[FIN,EUR,true,true,67.0]), (HG00271,[FIN,EUR,false,false,73.0]), (HG00272,[FIN,EUR,true,true,71.0]), (HG00273,[FIN,EUR,false,true,67.0]), (HG00280,[FIN,EUR,false,false,70.0]), (HG00290,[FIN,EUR,false,false,71.0]), (HG00304,[FIN,EUR,true,true,65.0]), (HG00311,[FIN,EUR,false,true,71.0]), (HG00321,[FIN,EUR,false,false,79.0]), (HG00323,[FIN,EUR,true,false,58.0]), (HG00324,[FIN,EUR,true,true,61.0]), (HG00326,[FIN,EUR,true,false,64.0]), (HG00332,[FIN,EUR,true,true,60.0]), (HG00334,[FIN,EUR,true,false,68.0]), (HG00343,[FIN,EUR,true,true,64.0]), (HG00356,[FIN,EUR,true,true,74.0]), 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(HG03470,[MSL,AFR,true,false,67.0]), (HG03472,[MSL,AFR,false,true,74.0]), (HG03485,[MSL,AFR,true,true,59.0]), (HG03491,[PJL,SAS,true,true,62.0]), (HG03511,[ESN,AFR,true,false,65.0]), (HG03514,[ESN,AFR,true,false,56.0]), (HG03515,[ESN,AFR,false,true,69.0]), (HG03521,[ESN,AFR,false,false,68.0]), (HG03547,[MSL,AFR,false,false,75.0]), (HG03558,[MSL,AFR,true,true,69.0]), (HG03565,[MSL,AFR,false,true,70.0]), (HG03575,[MSL,AFR,true,false,65.0]), (HG03593,[BEB,SAS,false,false,68.0]), (HG03595,[BEB,SAS,true,true,65.0]), (HG03607,[BEB,SAS,true,false,66.0]), (HG03624,[PJL,SAS,false,true,65.0]), (HG03634,[PJL,SAS,true,false,60.0]), (HG03636,[PJL,SAS,false,true,70.0]), (HG03643,[STU,SAS,true,false,62.0]), (HG03646,[STU,SAS,false,false,64.0]), (HG03668,[PJL,SAS,true,false,62.0]), (HG03690,[STU,SAS,true,true,63.0]), (HG03703,[PJL,SAS,true,false,69.0]), (HG03716,[ITU,SAS,false,false,64.0]), (HG03720,[ITU,SAS,false,true,66.0]), (HG03740,[STU,SAS,false,true,65.0]), (HG03765,[PJL,SAS,true,false,60.0]), (HG03767,[PJL,SAS,false,false,73.0]), (HG03780,[ITU,SAS,true,false,62.0]), (HG03784,[ITU,SAS,true,true,64.0]), (HG03790,[ITU,SAS,false,false,72.0]), (HG03792,[ITU,SAS,false,true,69.0]), (HG03793,[BEB,SAS,true,false,70.0]), (HG03802,[BEB,SAS,true,true,63.0]), (HG03821,[BEB,SAS,false,false,62.0]), (HG03824,[BEB,SAS,false,false,67.0]), (HG03830,[BEB,SAS,false,true,76.0]), (HG03832,[BEB,SAS,true,false,65.0]), (HG03848,[STU,SAS,false,false,59.0]), (HG03849,[STU,SAS,true,false,71.0]), (HG03857,[STU,SAS,true,true,58.0]), (HG03863,[ITU,SAS,true,false,61.0]), (HG03871,[ITU,SAS,false,false,65.0]), (HG03874,[ITU,SAS,true,false,65.0]), (HG03875,[ITU,SAS,false,false,63.0]), (HG03884,[STU,SAS,true,true,61.0]), (HG03898,[STU,SAS,true,true,68.0]), (HG03899,[STU,SAS,false,true,70.0]), (HG03900,[STU,SAS,false,false,66.0]), (HG03914,[BEB,SAS,false,true,64.0]), (HG03916,[BEB,SAS,true,false,70.0]), (HG03917,[BEB,SAS,false,false,68.0]), (HG03931,[BEB,SAS,true,true,62.0]), (HG03934,[BEB,SAS,true,false,64.0]), (HG03943,[STU,SAS,false,true,67.0]), (HG03944,[STU,SAS,true,true,63.0]), (HG03945,[STU,SAS,true,false,69.0]), (HG03949,[STU,SAS,true,true,66.0]), (HG03955,[STU,SAS,true,true,64.0]), (HG03968,[ITU,SAS,true,true,61.0]), (HG03976,[ITU,SAS,false,false,63.0]), (HG03995,[STU,SAS,true,false,64.0]), (HG04006,[STU,SAS,false,true,69.0]), (HG04022,[ITU,SAS,false,true,69.0]), (HG04025,[ITU,SAS,true,false,62.0]), (HG04038,[STU,SAS,true,false,68.0]), (HG04054,[ITU,SAS,true,true,64.0]), (HG04059,[ITU,SAS,true,true,66.0]), (HG04061,[ITU,SAS,false,false,74.0]), (HG04062,[ITU,SAS,true,true,57.0]), (HG04076,[ITU,SAS,true,true,64.0]), (HG04094,[ITU,SAS,false,false,58.0]), (HG04107,[STU,SAS,false,true,67.0]), (HG04140,[BEB,SAS,false,false,67.0]), (HG04141,[BEB,SAS,true,true,65.0]), (HG04146,[BEB,SAS,false,false,59.0]), (HG04161,[BEB,SAS,false,false,69.0]), (HG04164,[BEB,SAS,false,true,69.0]), (HG04171,[BEB,SAS,true,true,70.0]), (HG04176,[BEB,SAS,false,false,71.0]), (HG04182,[BEB,SAS,false,false,69.0]), (HG04186,[BEB,SAS,true,true,70.0]), (HG04189,[BEB,SAS,true,false,66.0]), (HG04194,[BEB,SAS,false,false,66.0]), (HG04195,[BEB,SAS,true,false,65.0]), (HG04210,[STU,SAS,false,false,65.0]), (HG04219,[ITU,SAS,false,false,66.0]), (HG04225,[ITU,SAS,false,true,68.0]), (HG04229,[STU,SAS,false,false,70.0]), (HG04235,[ITU,SAS,false,false,65.0]), (NA06989,[CEU,EUR,true,true,61.0]), (NA07000,[CEU,EUR,true,false,60.0]), (NA07037,[CEU,EUR,true,true,60.0]), (NA07357,[CEU,EUR,false,true,71.0]), (NA10847,[CEU,EUR,true,true,66.0]), (NA10851,[CEU,EUR,false,false,74.0]), (NA11840,[CEU,EUR,true,true,67.0]), (NA11894,[CEU,EUR,true,false,61.0]), (NA11918,[CEU,EUR,true,false,61.0]), (NA11920,[CEU,EUR,true,false,65.0]), (NA11932,[CEU,EUR,false,true,62.0]), (NA11933,[CEU,EUR,true,true,68.0]), (NA11992,[CEU,EUR,false,true,74.0]), (NA11994,[CEU,EUR,false,false,74.0]), (NA12046,[CEU,EUR,true,false,70.0]), (NA12156,[CEU,EUR,true,false,64.0]), (NA12272,[CEU,EUR,false,true,73.0]), (NA12282,[CEU,EUR,false,false,61.0]), (NA12283,[CEU,EUR,true,true,65.0]), (NA12340,[CEU,EUR,false,false,66.0]), (NA12347,[CEU,EUR,false,false,70.0]), (NA12400,[CEU,EUR,true,true,63.0]), (NA12546,[CEU,EUR,false,true,57.0]), (NA12717,[CEU,EUR,true,true,73.0]), (NA12749,[CEU,EUR,true,false,63.0]), (NA12751,[CEU,EUR,true,true,64.0]), (NA12760,[CEU,EUR,false,false,63.0]), (NA12761,[CEU,EUR,true,true,64.0]), (NA12814,[CEU,EUR,false,true,65.0]), (NA12830,[CEU,EUR,true,true,64.0]), (NA12890,[CEU,EUR,true,true,64.0]), (NA18488,[YRI,AFR,true,false,66.0]), (NA18505,[YRI,AFR,true,false,61.0]), (NA18510,[YRI,AFR,false,true,67.0]), (NA18526,[CHB,EAS,true,false,63.0]), (NA18533,[CHB,EAS,true,false,62.0]), (NA18535,[CHB,EAS,true,true,64.0]), (NA18536,[CHB,EAS,false,true,67.0]), (NA18542,[CHB,EAS,true,false,55.0]), (NA18550,[CHB,EAS,true,true,66.0]), (NA18552,[CHB,EAS,true,true,61.0]), (NA18558,[CHB,EAS,false,true,73.0]), (NA18560,[CHB,EAS,true,false,61.0]), (NA18571,[CHB,EAS,true,true,67.0]), (NA18577,[CHB,EAS,true,true,59.0]), (NA18582,[CHB,EAS,true,false,60.0]), (NA18595,[CHB,EAS,true,true,57.0]), (NA18596,[CHB,EAS,true,true,65.0]), (NA18603,[CHB,EAS,false,true,65.0]), (NA18608,[CHB,EAS,false,false,73.0]), (NA18609,[CHB,EAS,false,true,73.0]), (NA18610,[CHB,EAS,true,false,68.0]), (NA18613,[CHB,EAS,false,false,73.0]), (NA18615,[CHB,EAS,true,false,64.0]), (NA18618,[CHB,EAS,true,false,64.0]), (NA18620,[CHB,EAS,false,true,72.0]), (NA18622,[CHB,EAS,false,true,69.0]), (NA18623,[CHB,EAS,false,true,66.0]), (NA18624,[CHB,EAS,false,false,72.0]), (NA18626,[CHB,EAS,true,false,59.0]), (NA18636,[CHB,EAS,false,false,73.0]), (NA18638,[CHB,EAS,false,true,73.0]), (NA18639,[CHB,EAS,false,true,74.0]), (NA18641,[CHB,EAS,true,false,67.0]), (NA18646,[CHB,EAS,true,true,66.0]), (NA18648,[CHB,EAS,false,true,65.0]), (NA18740,[CHB,EAS,false,true,65.0]), (NA18867,[YRI,AFR,true,false,65.0]), (NA18871,[YRI,AFR,false,false,72.0]), (NA18874,[YRI,AFR,false,true,64.0]), (NA18912,[YRI,AFR,true,false,67.0]), (NA18915,[YRI,AFR,false,true,69.0]), (NA18933,[YRI,AFR,true,true,64.0]), (NA18949,[JPT,EAS,true,true,64.0]), (NA18950,[JPT,EAS,true,true,68.0]), (NA18951,[JPT,EAS,true,false,55.0]), (NA18953,[JPT,EAS,false,true,62.0]), (NA18956,[JPT,EAS,true,false,64.0]), (NA18957,[JPT,EAS,true,true,63.0]), (NA18964,[JPT,EAS,true,false,60.0]), (NA18970,[JPT,EAS,false,false,73.0]), (NA18975,[JPT,EAS,true,true,65.0]), (NA18978,[JPT,EAS,true,false,64.0]), (NA18981,[JPT,EAS,true,false,62.0]), (NA18982,[JPT,EAS,false,false,69.0]), (NA18983,[JPT,EAS,false,false,70.0]), (NA18985,[JPT,EAS,false,false,69.0]), (NA18987,[JPT,EAS,true,false,71.0]), (NA18990,[JPT,EAS,false,false,70.0]), (NA18991,[JPT,EAS,true,false,61.0]), (NA18999,[JPT,EAS,true,false,64.0]), (NA19003,[JPT,EAS,true,true,58.0]), (NA19006,[JPT,EAS,false,false,64.0]), (NA19007,[JPT,EAS,false,false,62.0]), (NA19010,[JPT,EAS,true,true,60.0]), (NA19011,[JPT,EAS,true,true,63.0]), (NA19024,[LWK,AFR,true,true,61.0]), (NA19026,[LWK,AFR,false,false,60.0]), (NA19031,[LWK,AFR,false,false,76.0]), (NA19037,[LWK,AFR,true,false,58.0]), (NA19041,[LWK,AFR,false,false,70.0]), (NA19055,[JPT,EAS,false,true,68.0]), (NA19057,[JPT,EAS,true,false,61.0]), (NA19058,[JPT,EAS,false,false,72.0]), (NA19059,[JPT,EAS,true,true,62.0]), (NA19060,[JPT,EAS,false,false,69.0]), (NA19062,[JPT,EAS,false,false,70.0]), (NA19063,[JPT,EAS,false,false,74.0]), (NA19064,[JPT,EAS,true,true,64.0]), (NA19065,[JPT,EAS,true,true,62.0]), (NA19079,[JPT,EAS,false,true,69.0]), (NA19082,[JPT,EAS,false,true,71.0]), (NA19086,[JPT,EAS,false,true,69.0]), (NA19095,[YRI,AFR,true,true,63.0]), (NA19102,[YRI,AFR,true,false,64.0]), (NA19119,[YRI,AFR,false,false,71.0]), (NA19129,[YRI,AFR,true,false,63.0]), (NA19147,[YRI,AFR,true,false,60.0]), (NA19159,[YRI,AFR,true,false,71.0]), (NA19172,[YRI,AFR,true,false,66.0]), (NA19185,[YRI,AFR,true,false,68.0]), (NA19189,[YRI,AFR,false,true,63.0]), (NA19197,[YRI,AFR,true,true,66.0]), (NA19200,[YRI,AFR,false,true,71.0]), (NA19238,[YRI,AFR,true,false,65.0]), (NA19247,[YRI,AFR,true,true,64.0]), (NA19248,[YRI,AFR,false,false,65.0]), (NA19257,[YRI,AFR,true,false,58.0]), (NA19315,[LWK,AFR,true,false,57.0]), (NA19320,[LWK,AFR,true,false,68.0]), (NA19332,[LWK,AFR,true,true,59.0]), (NA19338,[LWK,AFR,true,true,66.0]), (NA19372,[LWK,AFR,false,true,73.0]), (NA19375,[LWK,AFR,false,false,76.0]), (NA19379,[LWK,AFR,true,false,60.0]), (NA19384,[LWK,AFR,false,false,73.0]), (NA19393,[LWK,AFR,false,false,70.0]), (NA19397,[LWK,AFR,false,false,73.0]), (NA19401,[LWK,AFR,true,true,62.0]), (NA19404,[LWK,AFR,true,true,67.0]), (NA19435,[LWK,AFR,true,true,60.0]), (NA19443,[LWK,AFR,false,false,70.0]), (NA19446,[LWK,AFR,true,false,68.0]), (NA19449,[LWK,AFR,true,false,62.0]), (NA19455,[LWK,AFR,false,true,69.0]), (NA19457,[LWK,AFR,true,false,64.0]), (NA19466,[LWK,AFR,false,true,69.0]), (NA19468,[LWK,AFR,true,true,58.0]), (NA19471,[LWK,AFR,true,true,67.0]), (NA19473,[LWK,AFR,true,false,62.0]), (NA19474,[LWK,AFR,true,true,65.0]), (NA19625,[ASW,AFR,true,true,60.0]), (NA19655,[MXL,AMR,false,true,70.0]), (NA19663,[MXL,AMR,true,true,69.0]), (NA19681,[MXL,AMR,true,true,68.0]), (NA19703,[ASW,AFR,false,true,69.0]), (NA19707,[ASW,AFR,true,true,63.0]), (NA19711,[ASW,AFR,false,false,66.0]), (NA19716,[MXL,AMR,true,true,63.0]), (NA19717,[MXL,AMR,false,false,72.0]), (NA19722,[MXL,AMR,true,true,61.0]), (NA19728,[MXL,AMR,true,false,67.0]), (NA19731,[MXL,AMR,true,false,60.0]), (NA19747,[MXL,AMR,false,true,69.0]), (NA19764,[MXL,AMR,true,true,65.0]), (NA19770,[MXL,AMR,true...

Check the average call rate in the filtered data:

print(vdsGfilter.summarize().callRate)

Some(0.8356980125438334)

Remember, in the cmd 46, the call rate was 0.988. Now, the call rate is 0.84 because many genotypes were filtered out.

Filter samples

If your dataset is large, you can also afford to remove samples with low call rate.

Calculate the samples quality scores:

vdsGfilter = vdsGfilter.sampleQC()

vdsGfilter: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}},Empty,Genotype,true,false,false), rdd=OrderedRDD[88] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00114, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00150, HG00151, HG00159, HG00181, HG00182, HG00183, HG00185, HG00232, HG00235, HG00238, HG00239, HG00240, HG00242, HG00243, HG00244, HG00245, HG00246, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00269, HG00271, HG00272, HG00273, HG00280, HG00290, HG00304, HG00311, HG00321, HG00323, HG00324, HG00326, HG00332, HG00334, HG00343, HG00356, HG00362, HG00367, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00565, HG00566, HG00583, HG00584, HG00592, HG00593, HG00598, HG00620, HG00635, HG00650, HG00654, HG00675, HG00701, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG00879, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01168, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01437, HG01438, HG01464, HG01474, HG01479, HG01488, HG01501, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01672, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01989, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03022, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12272, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18609, NA18610, NA18613, NA18615, NA18618, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18871, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19082, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19468, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19711, NA19716, NA19717, NA19722, NA19728, NA19731, NA19747, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, 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[KHV,EAS,true,true,66.0,[0.882766170969802,9676,1285,5294,2644,1738,6120,0,0,0,4995,1125,7.1950186027283864,2.569114900931614,33.338879702356365,24.54857375666782,4382,4.44,1.521288837744534,null]], [KHV,EAS,false,true,65.0,[0.9986315117233829,10946,15,6125,2810,2011,6832,0,0,0,5518,1314,21.72501370363602,5.933967996065087,73.48821487301267,21.363666943591117,4821,4.199391171993912,1.3973147687717553,null]], [ACB,AFR,true,false,71.0,[0.825107198248335,9044,1917,4671,2988,1385,5758,0,0,0,4669,1089,6.48872180451126,2.3622100767526284,33.70510835913317,25.886640324292387,4373,4.287419651056014,2.1574007220216607,null]], [PEL,AMR,false,false,66.0,[0.7789435270504516,8538,2423,4555,2467,1516,5499,0,0,0,4439,1060,6.460763644881702,2.350255435374133,31.739868821738,24.829385602443566,3983,4.187735849056604,1.6273087071240107,null]], [PEL,AMR,true,false,64.0,[0.8213666636255816,9003,1958,4745,2673,1585,5843,0,0,0,4708,1135,6.826724425191607,2.5664054151247413,33.35910252138167,25.489546595051056,4258,4.1480176211453745,1.686435331230284,null]], [ACB,AFR,false,false,67.0,[0.7190949730863972,7882,3079,3997,2566,1319,5204,0,0,0,4177,1027,5.631565592489207,1.9355272484739017,27.75501141842173,21.417497557016137,3885,4.067185978578384,1.9454131918119788,null]], [PEL,AMR,false,true,75.0,[0.8449046619833956,9261,1700,5023,2474,1764,6002,0,0,1,4849,1153,7.053018032609878,2.620448360651264,33.178274484396816,25.292139689539567,4238,4.205550737207285,1.4024943310657596,null]], [PEL,AMR,false,true,75.0,[0.8804853571754402,9651,1310,5482,2352,1817,5986,0,0,0,4837,1149,7.930680758470614,3.129482596678124,34.945394259662265,24.891662935997022,4169,4.209747606614448,1.294441386901486,null]], [PEL,AMR,false,false,76.0,[0.8984581698750114,9848,1113,5659,2262,1927,6116,0,0,0,4955,1161,8.557778229082027,3.264459246207789,36.43805848903332,24.852632708150434,4189,4.267872523686477,1.1738453554748314,null]], [PEL,AMR,true,false,69.0,[0.8333181279080376,9134,1827,4982,2642,1510,5662,0,0,0,4602,1060,6.989270856141877,2.6027168382696972,32.82712940661265,24.09299741296742,4152,4.341509433962264,1.7496688741721855,null]], [PEL,AMR,true,false,69.0,[0.9290210747194599,10183,778,5694,2678,1811,6300,0,0,0,5094,1206,8.996857507610747,3.427105984597146,39.70097220858286,26.28841695854479,4489,4.223880597014926,1.4787410270568746,null]], [PEL,AMR,false,true,74.0,[0.9399689809323967,10303,658,5708,2714,1881,6476,0,0,0,5262,1214,9.01368533436862,3.2149840628375017,40.047558963408775,26.709974915437478,4595,4.334431630971993,1.442849548112706,null]], [PEL,AMR,true,true,60.0,[0.8949913329075814,9810,1151,5511,2515,1784,6083,0,0,1,4911,1172,7.722120285423056,2.868872273937178,34.020998980631944,24.00074683303253,4299,4.190273037542662,1.4097533632286996,null]], [PEL,AMR,false,false,70.0,[0.6669099534713986,7310,3651,3972,1911,1427,4765,0,0,0,3870,895,5.535841313269479,1.8447288596945064,25.463611491108075,19.737677139385923,3338,4.324022346368715,1.3391730903994394,null]], [PEL,AMR,true,true,68.0,[0.7109752759784691,7793,3168,4066,2440,1287,5014,0,0,1,4067,947,5.565764147311701,1.9064663301908191,27.101629667650474,20.94460411631165,3727,4.2946145723336855,1.895881895881896,null]], [PEL,AMR,false,false,71.0,[0.9893257914423866,10844,117,6103,2844,1897,6638,0,0,0,5376,1262,12.52194762080412,4.117978150609569,51.5641829583177,27.459554659079448,4741,4.259904912836767,1.4992092778070638,null]], [PEL,AMR,true,true,67.0,[0.9907855122707783,10860,101,6052,2839,1969,6777,0,0,0,5507,1270,13.085543278084664,4.2180172422869635,53.1891344383056,27.09011888567043,4808,4.336220472440945,1.4418486541391569,null]], [PEL,AMR,false,false,80.0,[0.9877748380622206,10827,134,6159,2594,2074,6742,0,0,0,5451,1291,12.311443613189237,3.9720299008019486,49.92204673501424,26.880031369014777,4668,4.222308288148722,1.2507232401157184,null]], [PEL,AMR,false,true...

Extract the samples scores:

val saDF = vdsGfilter.samplesKT().flatten.toDF(hc.sqlContext)
display(saDF)

Make a plot for sa.qc.callRate:

display(saDF)

Apply the filter:

var vdsGSfilter = vdsGfilter.filterSamplesExpr("sa.qc.callRate >= 0.60")

vdsGSfilter: is.hail.variant.VariantSampleMatrix[is.hail.variant.Genotype] = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}},Empty,Genotype,true,false,false), rdd=OrderedRDD[101] at RDD at OrderedRDD.scala:309, sampleIds=ArrayBuffer(HG00096, HG00100, HG00105, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00159, HG00181, HG00185, HG00235, HG00238, HG00239, HG00240, HG00243, HG00244, HG00245, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00271, HG00273, HG00290, HG00304, HG00321, HG00324, HG00332, HG00334, HG00356, HG00362, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00583, HG00584, HG00593, HG00598, HG00654, HG00675, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01438, HG01464, HG01474, HG01479, HG01488, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18610, NA18615, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19716, NA19717, NA19731, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=667, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0,[0.6757595109935225,7407,3554,3886,2358,1163,4684,0,0,0,3830,854,5.612663696503294,2.015256114928734,29.660456325097865,23.822554747761373,3521,4.484777517564403,2.0275150472914873,null]], [GBR,EUR,true,false,59.0,[0.9904205820636803,10856,105,6051,3067,1738,6543,0,0,0,5321,1222,12.789885777450271,3.892197491573195,53.19270449521008,27.411357878311442,4805,4.354337152209492,1.7646720368239355,null]], [GBR,EUR,false,false,77.0,[0.8772922178633337,9616,1345,5325,2719,1572,5863,0,0,0,4718,1145,7.258215474209669,2.6492050376055616,34.408277870216395,25.737756367987796,4291,4.120524017467249,1.729643765903308,null]], [GBR,EUR,false,true,71.0,[0.9249156098896086,10138,823,5664,2823,1651,6125,0,0,0,4970,1155,8.002663247188762,2.9466708696558412,36.569737620832356,25.785484690121354,4474,4.303030303030303,1.7098728043609934,null]], 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[KHV,EAS,true,true,68.0,[0.8878751938691726,9732,1229,5295,2723,1714,6151,0,0,0,4940,1211,9.530620632963451,4.276051355198048,41.96085080147955,27.365870790268538,4437,4.079273327828241,1.5886814469078179,null]], [KHV,EAS,true,true,63.0,[0.8511084755040599,9329,1632,5030,2586,1713,6012,0,0,1,4894,1118,6.913602744131192,2.515220338039457,32.838031943402314,25.15202840281304,4299,4.377459749552773,1.5096322241681261,null]], [ACB,AFR,false,true,71.0,[0.8594106377155369,9420,1541,5142,2681,1597,5875,0,0,1,4793,1082,7.83301486199576,3.126700511893367,35.430997876857795,24.9921816832534,4278,4.429759704251387,1.6787726988102694,null]], [PEL,AMR,false,false,69.0,[0.7381625764072621,8091,2870,4382,2153,1556,5265,0,0,0,4294,971,6.311457174638478,2.3144564008811344,29.665925101965104,23.182189632294165,3709,4.422245108135942,1.3836760925449871,null]], [CDX,EAS,true,true,62.0,[0.6607973725025089,7243,3718,3833,2127,1283,4693,0,0,0,3766,927,5.535137374016288,1.898203498191317,26.616181140411353,20.532073970190535,3410,4.062567421790723,1.6578332034294623,null]], [CDX,EAS,true,false,67.0,[0.6829668825837059,7486,3475,3929,2253,1304,4861,0,0,0,3920,941,5.326609671386591,1.7429848459806458,25.475420785466...

Check the results of filtering:

print(vdsGSfilter.summarize().samples)

667

There were 710 samples before, now there are 667 samples.

val saDFfilter = vdsGSfilter.samplesKT().flatten.toDF(hc.sqlContext)
display(saDFfilter)

Filter variants

We recommend to use the GATK Best Practices for assistance to define cut-off for variant scores.

First, we will annotate the variants because we removed some genotypes and samples, and this changed the scores. We will also use cache() for better performance.

vdsGSfilter = vdsGSfilter.variantQC().cache()

vdsGSfilter: is.hail.variant.VariantSampleMatrix[is.hail.variant.Genotype] = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}},Empty,Genotype,true,false,false), rdd=OrderedRDD[114] at RDD at OrderedRDD.scala:309, sampleIds=ArrayBuffer(HG00096, HG00100, HG00105, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00159, HG00181, HG00185, HG00235, HG00238, HG00239, HG00240, HG00243, HG00244, HG00245, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00271, HG00273, HG00290, HG00304, HG00321, HG00324, HG00332, HG00334, HG00356, HG00362, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00583, HG00584, HG00593, HG00598, HG00654, HG00675, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01438, HG01464, HG01474, HG01479, HG01488, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18610, NA18615, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19716, NA19717, NA19731, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=667, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0,[0.6757595109935225,7407,3554,3886,2358,1163,4684,0,0,0,3830,854,5.612663696503294,2.015256114928734,29.660456325097865,23.822554747761373,3521,4.484777517564403,2.0275150472914873,null]], [GBR,EUR,true,false,59.0,[0.9904205820636803,10856,105,6051,3067,1738,6543,0,0,0,5321,1222,12.789885777450271,3.892197491573195,53.19270449521008,27.411357878311442,4805,4.354337152209492,1.7646720368239355,null]], [GBR,EUR,false,false,77.0,[0.8772922178633337,9616,1345,5325,2719,1572,5863,0,0,0,4718,1145,7.258215474209669,2.6492050376055616,34.408277870216395,25.737756367987796,4291,4.120524017467249,1.729643765903308,null]], [GBR,EUR,false,true,71.0,[0.9249156098896086,10138,823,5664,2823,1651,6125,0,0,0,4970,1155,8.002663247188762,2.9466708696558412,36.569737620832356,25.785484690121354,4474,4.303030303030303,1.7098728043609934,null]], [GBR,EUR,false,false,71.0,[0.687619742724204,7537,3424,3947,2343,1247,4837,0,0,0,3930,907,5.499004909115026,1.9002678713434937,25.593472203794555,18.945864648879844,3590,4.3329658213891955,1.8789093825180434,null]], [GBR,EUR,false,true,70.0,[0.7367940881306451,8076,2885,4289,2513,1274,5061,0,0,0,4096,965,5.767582961862295,2.0121828431781066,27.51250619118376,20.82843351060116,3787,4.244559585492228,1.9725274725274726,null]], [GBR,EUR,true,true,68.0,[0.7221968798467293,7916,3045,4231,2517,1168,4853,0,0,1,3955,898,5.642117230924713,1.9276032093757203,26.644517433046985,19.79958219982416,3685,4.404231625835189,2.1549657534246576,null]], [GBR,EUR,true,true,67.0,[0.881032752486087,9657,1304,5351,2725,1581,5887,0,0,0,4757,1130,7.825618722170412,3.0227185399341177,36.53608781194976,26.328926126568696,4306,4.209734513274336,1.7235926628716003,null]], [GBR,EUR,false,false,72.0,[0.7242039959857677,7938,3023,4188,2551,1199,4949,0,0,0,4003,946,5.713655832703461,1.9622328444708734,27.19236583522303,20.29521741713476,3750,4.231501057082452,2.127606338615513,null]], [GBR,EUR,false,false,74.0,[0.6504880941519934,7130,3831,3656,2302,1172,4646,0,0,0,3727,919,5.564796633941088,1.9428931144801642,27.429312762973332,21.148837658611793,3474,4.055495103373231,1.9641638225255973,null]], [GBR,EUR,false,false,78.0,[0.9515555150077548,10430,531,5832,2889,1709,6307,0,0,0,5127,1180,9.205081495685539,3.3320307076458673,41.32770853307751,27.506993606026555,4598,4.344915254237288,1.6904622586307783,null]], [GBR,EUR,false,false,77.0,[0.9889608612352887,10840,121,6097,2924,1819,6562,0,0,0,5316,1246,12.314667896678959,3.9129323359027253,51.021586715867,27.36745809891719,4743,4.26645264847512,1.6074766355140186,null]], [GBR,EUR,false,false,64.0,[0.6498494662895721,7123,3838,3700,2302,1121,4544,0,0,2,3691,853,5.3120876035378375,1.8338706231609372,24.753895830408553,17.93072282975864,3423,4.327080890973036,2.0535236396074934,null]], [FIN,EUR,false,true,62.0,[0.9050269136027734,9920,1041,5491,2839,1590,6019,0,0,0,4870,1149,7.459879032258052,2.6206383090112038,35.25070564516124,25.953982802113213,4429,4.2384682332463015,1.7855345911949685,null]], 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Then we will extract the annotation score to a data frame and show its content.

val vaDF = vdsGSfilter.variantsKT().flatten.toDF(hc.sqlContext)
display(vaDF)

Visualize any variant annotation score with Databricks plot options:

display(vaDF)

var vdsGSVfilter = vdsGSfilter.filterVariantsExpr("va.info.MQ >= 55.0 && va.info.QD >= 5.0")

vdsGSVfilter: is.hail.variant.VariantSampleMatrix[is.hail.variant.Genotype] = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}},Empty,Genotype,true,false,false), rdd=OrderedRDD[123] at RDD at OrderedRDD.scala:309, sampleIds=ArrayBuffer(HG00096, HG00100, HG00105, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00159, HG00181, HG00185, HG00235, HG00238, HG00239, HG00240, HG00243, HG00244, HG00245, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00271, HG00273, HG00290, HG00304, HG00321, HG00324, HG00332, HG00334, HG00356, HG00362, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00583, HG00584, HG00593, HG00598, HG00654, HG00675, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01438, HG01464, HG01474, HG01479, HG01488, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18610, NA18615, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19716, NA19717, NA19731, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=667, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0,[0.6757595109935225,7407,3554,3886,2358,1163,4684,0,0,0,3830,854,5.612663696503294,2.015256114928734,29.660456325097865,23.822554747761373,3521,4.484777517564403,2.0275150472914873,null]], [GBR,EUR,true,false,59.0,[0.9904205820636803,10856,105,6051,3067,1738,6543,0,0,0,5321,1222,12.789885777450271,3.892197491573195,53.19270449521008,27.411357878311442,4805,4.354337152209492,1.7646720368239355,null]], 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[PEL,AMR,false,false,76.0,[0.8984581698750114,9848,1113,5659,2262,1927,6116,0,0,0,4955,1161,8.557778229082027,3.264459246207789,36.43805848903332,24.852632708150434,4189,4.267872523686477,1.1738453554748314,null]], [PEL,AMR,true,false,69.0,[0.8333181279080376,9134,1827,4982,2642,1510,5662,0,0,0,4602,1060,6.989270856141877,2.6027168382696972,32.82712940661265,24.09299741296742,4152,4.341509433962264,1.7496688741721855,null]], [PEL,AMR,true,false,69.0,[0.9290210747194599,10183,778,5694,2678,1811,6300,0,0,0,5094,1206,8.996857507610747,3.427105984597146,39.70097220858286,26.28841695854479,4489,4.223880597014926,1.4787410270568746,null]], [PEL,AMR,false,true,74.0,[0.9399689809323967,10303,658,5708,2714,1881,6476,0,0,0,5262,1214,9.01368533436862,3.2149840628375017,40.047558963408775,26.709974915437478,4595,4.334431630971993,1.442849548112706,null]], [PEL,AMR,true,true,60.0,[0.8949913329075814,9810,1151,5511,2515,1784,6083,0,0,1,4911,1172,7.722120285423056,2.868872273937178,34.020998980631944,24.00074683303253,4299,4.190273037542662,1.4097533632286996,null]], [PEL,AMR,false,false,70.0,[0.6669099534713986,7310,3651,3972,1911,1427,4765,0,0,0,3870,895,5.535841313269479,1.8447288596945064,25.463611491108075,19.737677139385923,3338,4.324022346368715,1.3391730903994394,null]], [PEL,AMR,true,true,68.0,[0.7109752759784691,7793,3168,4066,2440,1287,5014,0,0,1,4067,947,5.565764147311701,1.9064663301908191,27.101629667650474,20.94460411631165,3727,4.2946145723336855,1.895881895881896,null]], [PEL,AMR,false,false,71.0,[0.9893257914423866,10844,117,6103,2844,1897,6638,0,0,0,5376,1262,12.52194762080412,4.117978150609569,51.5641829583177,27.459554659079448,4741,4.259904912836767,1.4992092778070638,null]], [PEL,AMR,true,true,67.0,[0.9907855122707783,10860,101,6052,2839,1969,6777,0,0,0,5507,1270,13.085543278084664,4.2180172422869635,53.1891344383056,27.09011888567043,4808,4.336220472440945,1.4418486541391569,null]], [PEL,AMR,false,false,80.0,[0.9877748380622206,10827,134,6159,2594,2074,6742,0,0,0,5451,1291,12.311443613189237,3.9720299008019486,49.92204673501424,26.880031369014777,4668,4.222308288148722,1.2507232401157184,null]], [PEL,AMR,false,true,74.0,[0.9919715354438464,10873,88,6131,2859,1883,6625,0,0,0,5341,1284,12.83169318495356,3.938434499197187,53.151660075416245,27.5213568275164,4742,4.159657320872274,1.5183218268720127,null]], [PEL,AMR,true,false,69.0,[0.7412644831675942,8125,2836,4339,2306,1480,5266,0,0,1,4293,973,6.246892307692317,2.299986194761761,29.39323076923076,22.901637503273893,3786,4.4121274409044196,1.558108108108108,null]], [PEL,AMR,false,false,68.0,[0.8998266581516285,9863,1098,5468,2647,1748,6143,0,0,1,4996,1147,8.64726756564944,3.3664290210452346,39.37625468924261,27.45593414668313,4395,4.355710549258936,1.5143020594965675,null]], [KHV,EAS,false,true,76.0,[0.8558525681963325,9381,1580,5150,2542,1689,5920,0,0,0,4727,1193,7.101481718366889,2.572131551634195,32.552712930391316,24.10621502343747,4231,3.9622799664710815,1.5050325636471285,null]], [KHV,EAS,true,true,64.0,[0.7050451601131283,7728,3233,4070,2299,1359,5017,0,0,0,4086,931,5.759963768115961,2.045349367700865,27.841097308488607,21.282710992768532,3658,4.388829215896885,1.6916850625459896,null]], [KHV,EAS,true,false,65.0,[0.7806769455341666,8557,2404,4646,2422,1489,5400,0,0,0,4368,1032,9.194811265630392,5.102184185835582,39.70503681196681,26.923442275128917,3911,4.232558139534884,1.6265950302216252,null]], [KHV,EAS,false,true,68.0,[0.9438007481069246,10345,616,5695,2687,1963,6613,0,0,0,5364,1249,9.008119864668899,3.4307809454603664,39.50633156114064,26.310239329947265,4650,4.294635708566854,1.3688232297503822,null]], [KHV,EAS,false,true,76.0,[0.8173524313475048,8959,2002,4865,2524,1570,5664,0,0,0,4587,1077,6.530304721509105,2.3207360113434956,30.777095657997535,23.563907019716094,4094,4.259052924791086,1.607643312101911,null]], [KHV,EAS,true,true,66.0,[0.9906942797190037,10859,102,6069,2797,1993,6783,0,0,0,5501,1282,12.427295331061812,3.943978143155647,51.30260613316141,27.342852968519832,4790,4.290951638065523,1.403411941796287,null]], [ACB,AFR,false,false,68.0,[0.8126995712070066,8908,2053,4624,2692,1592,5876,0,0,1,4772,1104,6.666928603502492,2.4482240011094647,33.01414458913336,25.305205287824293,4284,4.322463768115942,1.6909547738693467,null]], [KHV,EAS,true,true,67.0,[0.9959857677219232,10917,44,6005,2946,1966,6878,0,0,1,5553,1325,13.780525785472229,4.311071611905572,55.04369332234146,26.756074625849152,4912,4.190943396226415,1.4984740590030519,null]], [KHV,EAS,false,true,69.0,[0.7231092053644741,7926,3035,4234,2243,1449,5141,0,0,0,4183,958,6.133106232652048,2.2550185969612198,29.427706283118795,22.98846674515266,3692,4.366388308977036,1.5479641131815045,null]], [KHV,EAS,true,true,64.0,[0.9957120700665998,10914,47,6007,2939,1968,6875,0,0,0,5567,1308,13.208905992303414,4.029687503515549,54.68343412131193,27.485410634962367,4907,4.25611620795107,1.4933943089430894,null]], [KHV,EAS,false,false,67.0,[0.9929750935133655,10884,77,6010,2841,2033,6907,0,0,0,5585,1322,12.989801543550236,4.047833572536901,53.46343256155825,27.331365358424808,4874,4.224659606656581,1.397442203639941,null]], [KHV,EAS,true,true,67.0,[0.9108657969163397,9984,977,5425,2750,1809,6368,0,0,0,5159,1209,8.551081730769228,3.335295120584832,39.559294871794876,27.5133579471579,4559,4.267162944582299,1.5201768933112216,null]], [KHV,EAS,true,true,67.0,[0.8420764528783871,9230,1731,4996,2634,1600,5834,0,0,0,4731,1103,8.60563380281688,3.8611674375430214,39.199458288190556,26.97736661658623,4234,4.28921124206709,1.64625,null]], [PEL,AMR,true,true,68.0,[0.9406988413465924,10311,650,5763,2690,1858,6406,0,0,0,5215,1191,11.61478033168461,5.08753659048692,47.84017069149458,27.836793496827248,4548,4.378673383711167,1.4477933261571583,null]], [ACB,AFR,true,false,66.0,[0.9592190493568105,10514,447,5766,2923,1825,6573,0,0,1,5314,1259,11.186798554308552,4.342843960969613,47.32918014076483,27.412006153706123,4748,4.220810166799047,1.6016438356164384,null]], [PEL,AMR,true,false,66.0,[0.9482711431438737,10394,567,5867,2578,1949,6476,0,0,0,5263,1213,8.398499134115841,2.955174974340417,37.63344237059855,26.299146824005057,4527,4.338829348722176,1.3227296049256028,null]], [PEL,AMR,false,true,64.0,[0.9351336556883496,10250,711,5816,2513,1921,6355,0,0,0,5158,1197,12.112878048780475,5.477585368840255,48.60419512195132,27.721414139851273,4434,4.309106098579782,1.308172826652785,null]], [ACB,AFR,true,true,63.0,[0.8680777301341118,9515,1446,5163,2738,1614,5966,0,0,1,4817,1149,7.754703100367829,3.034492152029938,35.40462427745657,25.028484448565706,4352,4.192341166231506,1.6964064436183395,null]], [ACB,AFR,true,true,65.0,[0.8544840799197153,9366,1595,5081,2729,1556,5841,0,0,2,4724,1117,7.476510783685676,2.91146922360095,34.29660474055091,24.329983838993222,4285,4.229185317815578,1.7538560411311055,null]], [KHV,EAS,true,true,67.0,[0.9129641456071527,10007,954,5475,2765,1767,6299,0,0,0,5073,1226,9.931348056360514,4.288695439812574,43.44358948735903,27.519979036224832,4532,4.137846655791191,1.5647990945104697,null]], [KHV,EAS,true,false,69.0,[0.9045707508439012,9915,1046,5483,2673,1759,6191,0,0,0,5003,1188,9.061220373171968,3.728640149024342,40.40191628845173,27.08202248475741,4432,4.211279461279461,1.519613416714042,null]], [KHV,EAS,true,true,68.0,[0.8878751938691726,9732,1229,5295,2723,1714,6151,0,0,0,4940,1211,9.530620632963451,4.276051355198048,41.96085080147955,27.365870790268538,4437,4.079273327828241,1.5886814469078179,null]], [KHV,EAS,true,true,63.0,[0.8511084755040599,9329,1632,5030,2586,1713,6012,0,0,1,4894,1118,6.913602744131192,2.515220338039457,32.838031943402314,25.15202840281304,4299,4.377459749552773,1.5096322241681261,null]], [ACB,AFR,false,true,71.0,[0.8594106377155369,9420,1541,5142,2681,1597,5875,0,0,1,4793,1082,7.83301486199576,3.126700511893367,35.430997876857795,24.9921816832534,4278,4.429759704251387,1.6787726988102694,null]], [PEL,AMR,false,false,69.0,[0.7381625764072621,8091,2870,43...

Check how many sites have been removed:

print(vdsGSVfilter.summarize().variants)

10660

There were 10961 variants beofre filtering. Now, there 10660 variant sites.

You can also make plots for the scores from the filtered dataset to make sure that all the filter worked as intended.

val vaDFfilter = vdsGSVfilter.variantsKT().flatten.toDF(hc.sqlContext)

vaDFfilter: org.apache.spark.sql.DataFrame = [v: struct<contig: string, start: int ... 2 more fields>, va.rsid: string ... 37 more fields]

display(vaDFfilter)

Write the filtered VDS to a file for future analyses

val out_path = "/1kg_filtered.vds"
vdsGSVfilter.write(out_path, overwrite=true)

out_path: String = /1kg_filtered.vds

After that you can simply load this already filtered file for the future analyses.

val vdsFiltered = hc.readVDS(out_path)

vdsFiltered: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}},Empty,Genotype,true,false,false), rdd=OrderedRDD[143] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00159, HG00181, HG00185, HG00235, HG00238, HG00239, HG00240, HG00243, HG00244, HG00245, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00271, HG00273, HG00290, HG00304, HG00321, HG00324, HG00332, HG00334, HG00356, HG00362, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00583, HG00584, HG00593, HG00598, HG00654, HG00675, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01438, HG01464, HG01474, HG01479, HG01488, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18610, NA18615, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, 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[KHV,EAS,false,true,68.0,[0.9438007481069246,10345,616,5695,2687,1963,6613,0,0,0,5364,1249,9.008119864668899,3.4307809454603664,39.50633156114064,26.310239329947265,4650,4.294635708566854,1.3688232297503822,null]], [KHV,EAS,false,true,76.0,[0.8173524313475048,8959,2002,4865,2524,1570,5664,0,0,0,4587,1077,6.530304721509105,2.3207360113434956,30.777095657997535,23.563907019716094,4094,4.259052924791086,1.607643312101911,null]], [KHV,EAS,true,true,66.0,[0.9906942797190037,10859,102,6069,2797,1993,6783,0,0,0,5501,1282,12.427295331061812,3.943978143155647,51.30260613316141,27.342852968519832,4790,4.290951638065523,1.403411941796287,null]], [ACB,AFR,false,false,68.0,[0.8126995712070066,8908,2053,4624,2692,1592,5876,0,0,1,4772,1104,6.666928603502492,2.4482240011094647,33.01414458913336,25.305205287824293,4284,4.322463768115942,1.6909547738693467,null]], [KHV,EAS,true,true,67.0,[0.9959857677219232,10917,44,6005,2946,1966,6878,0,0,1,5553,1325,13.780525785472229,4.311071611905572,55.04369332234146,26.756074625849152,4912,4.190943396226415,1.4984740590030519,null]], [KHV,EAS,false,true,69.0,[0.7231092053644741,7926,3035,4234,2243,1449,5141,0,0,0,4183,958,6.133106232652048,2.2550185969612198,29.427706283118795,22.98846674515266,3692,4.366388308977036,1.5479641131815045,null]], [KHV,EAS,true,true,64.0,[0.9957120700665998,10914,47,6007,2939,1968,6875,0,0,0,5567,1308,13.208905992303414,4.029687503515549,54.68343412131193,27.485410634962367,4907,4.25611620795107,1.4933943089430894,null]], [KHV,EAS,false,false,67.0,[0.9929750935133655,10884,77,6010,2841,2033,6907,0,0,0,5585,1322,12.989801543550236,4.047833572536901,53.46343256155825,27.331365358424808,4874,4.224659606656581,1.397442203639941,null]], [KHV,EAS,true,true,67.0,[0.9108657969163397,9984,977,5425,2750,1809,6368,0,0,0,5159,1209,8.551081730769228,3.335295120584832,39.559294871794876,27.5133579471579,4559,4.267162944582299,1.5201768933112216,null]], [KHV,EAS,true,true,67.0,[0.8420764528783871,9230,1731,4996,2634,1600,5834,0,0,0,4731,1103,8.60563380281688,3.8611674375430214,39.199458288190556,26.97736661658623,4234,4.28921124206709,1.64625,null]], [PEL,AMR,true,true,68.0,[0.9406988413465924,10311,650,5763,2690,1858,6406,0,0,0,5215,1191,11.61478033168461,5.08753659048692,47.84017069149458,27.836793496827248,4548,4.378673383711167,1.4477933261571583,null]], [ACB,AFR,true,false,66.0,[0.9592190493568105,10514,447,5766,2923,1825,6573,0,0,1,5314,1259,11.186798554308552,4.342843960969613,47.32918014076483,27.412006153706123,4748,4.220810166799047,1.6016438356164384,null]], [PEL,AMR,true,false,66.0,[0.9482711431438737,10394,567,5867,2578,1949,6476,0,0,0,5263,1213,8.398499134115841,2.955174974340417,37.63344237059855,26.299146824005057,4527,4.338829348722176,1.3227296049256028,null]], [PEL,AMR,false,true,64.0,[0.9351336556883496,10250,711,5816,2513,1921,6355,0,0,0,5158,1197,12.112878048780475,5.477585368840255,48.60419512195132,27.721414139851273,4434,4.309106098579782,1.308172826652785,null]], [ACB,AFR,true,true,63.0,[0.8680777301341118,9515,1446,5163,2738,1614,5966,0,0,1,4817,1149,7.754703100367829,3.034492152029938,35.40462427745657,25.028484448565706,4352,4.192341166231506,1.6964064436183395,null]], [ACB,AFR,true,true,65.0,[0.8544840799197153,9366,1595,5081,2729,1556,5841,0,0,2,4724,1117,7.476510783685676,2.91146922360095,34.29660474055091,24.329983838993222,4285,4.229185317815578,1.7538560411311055,null]], [KHV,EAS,true,true,67.0,[0.9129641456071527,10007,954,5475,2765,1767,6299,0,0,0,5073,1226,9.931348056360514,4.288695439812574,43.44358948735903,27.519979036224832,4532,4.137846655791191,1.5647990945104697,null]], [KHV,EAS,true,false,69.0,[0.9045707508439012,9915,1046,5483,2673,1759,6191,0,0,0,5003,1188,9.061220373171968,3.728640149024342,40.40191628845173,27.08202248475741,4432,4.211279461279461,1.519613416714042,null]], [KHV,EAS,true,true,68.0,[0.8878751938691726,9732,1229,5295,2723,1714,6151,0,0,0,4940,1211,9.530620632963451,4.276051355198048,41.96085080147955,27.365870790268538,4437,4.079273327828241,1.5886814469078179,null]], [KHV,EAS,true,true,63.0,[0.8511084755040599,9329,1632,5030,2586,1713,6012,0,0,1,4894,1118,6.913602744131192,2.515220338039457,32.838031943402314,25.15202840281304,4299,4.377459749552773,1.5096322241681261,null]], [ACB,AFR,false,true,71.0,[0.8594106377155369,9420,1541,5142,2681,1597,5875,0,0,1,4793,1082,7.83301486199576,3.126700511893367,35.430997876857795,24.9921816832534,4278,4.429759704251387,1.6787726988102694,null]], [PEL,AMR,false,false,69.0,[0.7381625764072621,8091,2870,4382,2153,1556,5265,0,0,0,4294,9...

PCA

To show you a simple analysis you can do with such genetic data, we will check if there is any genetic structure in this data. We will use a principal component analysis (PCA) for that.

val VDSpca = vdsFiltered.pca("sa.pca", k=2)

2018-01-04 20:58:38 Hail: INFO: Running PCA with 2 components...
VDSpca: is.hail.variant.VariantDataset = VariantSampleMatrix(metadata=VSMMetadata(String,Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double},pca:Struct{PC1:Double,PC2:Double}},Variant,Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}},Empty,Genotype,true,false,false), rdd=OrderedRDD[143] at RDD at OrderedRDD.scala:309, sampleIds=WrappedArray(HG00096, HG00100, HG00105, HG00115, HG00116, HG00119, HG00120, HG00128, HG00131, HG00138, HG00140, HG00141, HG00159, HG00181, HG00185, HG00235, HG00238, HG00239, HG00240, HG00243, HG00244, HG00245, HG00250, HG00254, HG00257, HG00258, HG00261, HG00264, HG00271, HG00273, HG00290, HG00304, HG00321, HG00324, HG00332, HG00334, HG00356, HG00362, HG00371, HG00404, HG00410, HG00419, HG00446, HG00458, HG00463, HG00464, HG00472, HG00475, HG00478, HG00479, HG00533, HG00557, HG00583, HG00584, HG00593, HG00598, HG00654, HG00675, HG00702, HG00704, HG00705, HG00707, HG00737, HG00759, HG00766, HG00851, HG01047, HG01048, HG01055, HG01075, HG01080, HG01083, HG01085, HG01088, HG01092, HG01110, HG01112, HG01122, HG01130, HG01140, HG01142, HG01162, HG01164, HG01171, HG01173, HG01188, HG01242, HG01248, HG01251, HG01253, HG01259, HG01272, HG01275, HG01305, HG01308, HG01323, HG01334, HG01341, HG01344, HG01350, HG01351, HG01359, HG01363, HG01384, HG01390, HG01392, HG01412, HG01438, HG01464, HG01474, HG01479, HG01488, HG01503, HG01512, HG01525, HG01528, HG01531, HG01550, HG01577, HG01583, HG01598, HG01608, HG01617, HG01619, HG01620, HG01630, HG01631, HG01680, HG01686, HG01699, HG01765, HG01770, HG01771, HG01777, HG01786, HG01795, HG01798, HG01801, HG01804, HG01806, HG01809, HG01811, HG01812, HG01813, HG01816, HG01842, HG01853, HG01860, HG01861, HG01867, HG01869, HG01873, HG01880, HG01892, HG01893, HG01912, HG01917, HG01923, HG01926, HG01936, HG01939, HG01944, HG01945, HG01961, HG01965, HG01967, HG01973, HG01974, HG01979, HG01997, HG02002, HG02023, HG02028, HG02031, HG02032, HG02047, HG02048, HG02051, HG02057, HG02067, HG02075, HG02076, HG02086, HG02087, HG02089, HG02095, HG02102, HG02104, HG02108, HG02111, HG02113, HG02139, HG02140, HG02142, HG02143, HG02146, HG02152, HG02180, HG02187, HG02235, HG02252, HG02255, HG02259, HG02265, HG02271, HG02274, HG02281, HG02282, HG02283, HG02286, HG02292, HG02304, HG02309, HG02315, HG02322, HG02325, HG02334, HG02337, HG02343, HG02364, HG02372, HG02374, HG02377, HG02380, HG02381, HG02390, HG02406, HG02407, HG02419, HG02420, HG02449, HG02477, HG02484, HG02489, HG02491, HG02502, HG02505, HG02512, HG02537, HG02545, HG02555, HG02557, HG02562, HG02568, HG02577, HG02580, HG02589, HG02595, HG02604, HG02620, HG02624, HG02634, HG02642, HG02649, HG02651, HG02652, HG02654, HG02657, HG02666, HG02667, HG02675, HG02676, HG02682, HG02684, HG02685, HG02699, HG02722, HG02727, HG02734, HG02737, HG02763, HG02768, HG02769, HG02771, HG02774, HG02780, HG02787, HG02789, HG02807, HG02810, HG02814, HG02836, HG02852, HG02854, HG02855, HG02878, HG02884, HG02885, HG02888, HG02890, HG02895, HG02923, HG02938, HG02941, HG02944, HG02952, HG02979, HG02981, HG02983, HG03006, HG03021, HG03024, HG03028, HG03040, HG03060, HG03066, HG03081, HG03082, HG03085, HG03120, HG03121, HG03127, HG03129, HG03139, HG03157, HG03162, HG03166, HG03198, HG03199, HG03202, HG03209, HG03228, HG03240, HG03241, HG03247, HG03258, HG03259, HG03265, HG03267, HG03268, HG03270, HG03271, HG03291, HG03295, HG03351, HG03366, HG03367, HG03391, HG03397, HG03432, HG03452, HG03458, HG03470, HG03472, HG03485, HG03491, HG03511, HG03514, HG03515, HG03521, HG03547, HG03558, HG03565, HG03575, HG03593, HG03595, HG03607, HG03624, HG03634, HG03636, HG03643, HG03646, HG03668, HG03690, HG03703, HG03716, HG03720, HG03740, HG03765, HG03767, HG03780, HG03784, HG03790, HG03792, HG03793, HG03802, HG03821, HG03824, HG03830, HG03832, HG03848, HG03849, HG03857, HG03863, HG03871, HG03874, HG03875, HG03884, HG03898, HG03899, HG03900, HG03914, HG03916, HG03917, HG03931, HG03934, HG03943, HG03944, HG03945, HG03949, HG03955, HG03968, HG03976, HG03995, HG04006, HG04022, HG04025, HG04038, HG04054, HG04059, HG04061, HG04062, HG04076, HG04094, HG04107, HG04140, HG04141, HG04146, HG04161, HG04164, HG04171, HG04176, HG04182, HG04186, HG04189, HG04194, HG04195, HG04210, HG04219, HG04225, HG04229, HG04235, NA06989, NA07000, NA07037, NA07357, NA10847, NA10851, NA11840, NA11894, NA11918, NA11920, NA11932, NA11933, NA11992, NA11994, NA12046, NA12156, NA12282, NA12283, NA12340, NA12347, NA12400, NA12546, NA12717, NA12749, NA12751, NA12760, NA12761, NA12814, NA12830, NA12890, NA18488, NA18505, NA18510, NA18526, NA18533, NA18535, NA18536, NA18542, NA18550, NA18552, NA18558, NA18560, NA18571, NA18577, NA18582, NA18595, NA18596, NA18603, NA18608, NA18610, NA18615, NA18620, NA18622, NA18623, NA18624, NA18626, NA18636, NA18638, NA18639, NA18641, NA18646, NA18648, NA18740, NA18867, NA18874, NA18912, NA18915, NA18933, NA18949, NA18950, NA18951, NA18953, NA18956, NA18957, NA18964, NA18970, NA18975, NA18978, NA18981, NA18982, NA18983, NA18985, NA18987, NA18990, NA18991, NA18999, NA19003, NA19006, NA19007, NA19010, NA19011, NA19024, NA19026, NA19031, NA19037, NA19041, NA19055, NA19057, NA19058, NA19059, NA19060, NA19062, NA19063, NA19064, NA19065, NA19079, NA19086, NA19095, NA19102, NA19119, NA19129, NA19147, NA19159, NA19172, NA19185, NA19189, NA19197, NA19200, NA19238, NA19247, NA19248, NA19257, NA19315, NA19320, NA19332, NA19338, NA19372, NA19375, NA19379, NA19384, NA19393, NA19397, NA19401, NA19404, NA19435, NA19443, NA19446, NA19449, NA19455, NA19457, NA19466, NA19471, NA19473, NA19474, NA19625, NA19655, NA19663, NA19681, NA19703, NA19707, NA19716, NA19717, NA19731, NA19764, NA19770, NA19773, NA19776, NA19777, NA19782, NA19785, NA19788, NA19819, NA19834, NA19835, NA19917, NA19921, NA19982, NA19984, NA20276, NA20281, NA20298, NA20321, NA20336, NA20342, NA20351, NA20412, NA20506, NA20507, NA20509, NA20512, NA20514, NA20517, NA20518, NA20525, NA20531, NA20532, NA20536, NA20539, NA20544, NA20588, NA20589, NA20753, NA20756, NA20758, NA20765, NA20773, NA20774, NA20785, NA20786, NA20798, NA20801, NA20803, NA20807, NA20814, NA20815, NA20818, NA20821, NA20846, NA20847, NA20858, NA20863, NA20881, NA20886, NA20890, NA20898, NA20900, NA20908, NA20910, NA21086, NA21088, NA21091, NA21094, NA21097, NA21101, NA21104, NA21109, NA21111, NA21114, NA21119, NA21120, NA21125, NA21128, NA21130, NA21133, NA21137), nSamples=667, vaSignature=Struct{rsid:String,qual:Double,filters:Set[String],info:Struct{AC:Array[Int],AF:Array[Double],AN:Int,BaseQRankSum:Double,ClippingRankSum:Double,DP:Int,DS:Boolean,FS:Double,HaplotypeScore:Double,InbreedingCoeff:Double,MLEAC:Array[Int],MLEAF:Array[Double],MQ:Double,MQ0:Int,MQRankSum:Double,QD:Double,ReadPosRankSum:Double,set:String},qc:Struct{callRate:Double,AC:Int,AF:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rHeterozygosity:Double,rHetHomVar:Double,rExpectedHetFrequency:Double,pHWE:Double}}, saSignature=Struct{Population:String,SuperPopulation:String,isFemale:Boolean,PurpleHair:Boolean,CaffeineConsumption:Double,qc:Struct{callRate:Double,nCalled:Int,nNotCalled:Int,nHomRef:Int,nHet:Int,nHomVar:Int,nSNP:Int,nInsertion:Int,nDeletion:Int,nSingleton:Int,nTransition:Int,nTransversion:Int,dpMean:Double,dpStDev:Double,gqMean:Double,gqStDev:Double,nNonRef:Int,rTiTv:Double,rHetHomVar:Double,rInsertionDeletion:Double},pca:Struct{PC1:Double,PC2:Double}}, globalSignature=Empty, sampleAnnotations=ArrayBuffer([GBR,EUR,false,false,77.0,[0.6757595109935225,7407,3554,3886,2358,1163,4684,0,0,0,3830,854,5.612663696503294,2.015256114928734,29.660456325097865,23.822554747761373,3521,4.484777517564403,2.0275150472914873,null],[0.09751799008675095,0.17574257028619206]], 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[PEL,AMR,true,false,69.0,[0.9290210747194599,10183,778,5694,2678,1811,6300,0,0,0,5094,1206,8.996857507610747,3.427105984597146,39.70097220858286,26.28841695854479,4489,4.223880597014926,1.4787410270568746,null],[0.19193580495225934,-0.04513638619555292]], [PEL,AMR,false,true,74.0,[0.9399689809323967,10303,658,5708,2714,1881,6476,0,0,0,5262,1214,9.01368533436862,3.2149840628375017,40.047558963408775,26.709974915437478,4595,4.334431630971993,1.442849548112706,null],[0.23384471261880618,-0.16122624005969588]], [PEL,AMR,true,true,60.0,[0.8949913329075814,9810,1151,5511,2515,1784,6083,0,0,1,4911,1172,7.722120285423056,2.868872273937178,34.020998980631944,24.00074683303253,4299,4.190273037542662,1.4097533632286996,null],[0.19929775638592764,-0.04888376936847053]], [PEL,AMR,false,false,70.0,[0.6...

val pcaDF = VDSpca.samplesKT().flatten.toDF(hc.sqlContext)

pcaDF: org.apache.spark.sql.DataFrame = [s: string, sa.Population: string ... 26 more fields]

Replace dots in column names because they are not recognized correctly by SQL

val pcaDFrenamed = pcaDF.toDF(pcaDF.columns.map(_.replace(".", "_")): _*)
display(pcaDFrenamed)

Extract the PCA scores to a dataframe.

pcaDFrenamed.createOrReplaceTempView("PCA") 
val pc12DF = spark.sql("SELECT sa_SuperPopulation as pop, sa_pca_PC1 as PC1, sa_pca_PC2 as PC2 from PCA")
display(pc12DF)

Truncated to 30 rows

Make a scatterplot with PC1 and PC2, and add Pop as a grouping key.

display(pc12DF)

Truncated to 30 rows

You can see from this PCA that human genetic data is not homogeneous. There is a clear genetic differentiation between populations.

Visualization

This pipeline can also be modified to make plots with R instead of Databricks' display(). R allows making more complex and more flexible plots.

Below is an example of an R plot for the PCA. The same approach can be applied to all plots above.

Create an R dataframe from a Spark object:

rPCAdf <- as.data.frame(sql("SELECT sa_SuperPopulation as Population, sa_pca_PC1 as PC1, sa_pca_PC2 as PC2 from PCA"))
head(rPCAdf)

Using your favourite R library (ggplot2 in this case), make a plot:

library(ggplot2)

ggplot(rPCAdf, aes(x = PC1, y = PC2, color = Population)) + geom_point()

Summary

Data filtering:

• Filter genotypes
• Filter samples
• Filter variants

Variants can be filtered before samples filtering if samples are of greater priority in a study.

Such genetic data can be analyzed in various ways. A PCA is just one simple example.