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Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics

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Title Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics
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Keywords cloud VCF variant alleles site ADAM representation Format genotype multiallelic sample genotypes record — records GT ALT Genome Project triallelic reference
Keywords consistency
Keyword Content Title Description Headings
VCF 16
variant 11
alleles 9
site 8
ADAM 7
representation 7
Headings
H1 H2 H3 H4 H5 H6
2 2 2 0 0 0
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SEO Keywords (Single)

Keyword Occurrence Density
VCF 16 0.80 %
variant 11 0.55 %
alleles 9 0.45 %
site 8 0.40 %
ADAM 7 0.35 %
representation 7 0.35 %
Format 7 0.35 %
genotype 6 0.30 %
multiallelic 6 0.30 %
sample 5 0.25 %
genotypes 5 0.25 %
record 4 0.20 %
— 4 0.20 %
records 4 0.20 %
GT 3 0.15 %
ALT 3 0.15 %
Genome 3 0.15 %
Project 3 0.15 %
triallelic 3 0.15 %
reference 3 0.15 %

SEO Keywords (Two Word)

Keyword Occurrence Density
of the 5 0.25 %
the variant 4 0.20 %
1000 Genome 3 0.15 %
equivalent representation 3 0.15 %
VCF Format 3 0.15 %
this case 3 0.15 %
representation in 3 0.15 %
in ADAMAvro 3 0.15 %
from 1000 3 0.15 %
from the 3 0.15 %
Genome Project 3 0.15 %
the genotype 3 0.15 %
to a 3 0.15 %
is a 3 0.15 %
VCF file 3 0.15 %
multiallelic variant 3 0.15 %
or more 3 0.15 %
two or 3 0.15 %
genotypes contain 3 0.15 %
contain alleles 2 0.10 %

SEO Keywords (Three Word)

Keyword Occurrence Density Possible Spam
1000 Genome Project 3 0.15 % No
two or more 3 0.15 % No
from 1000 Genome 3 0.15 % No
representation in ADAMAvro 3 0.15 % No
equivalent representation in 3 0.15 % No
REF ALT QUAL 2 0.10 % No
a multiallelic variant 2 0.10 % No
ADAM Format — 2 0.10 % No
Variant Call Format 2 0.10 % No
Call Format VCF 2 0.10 % No
the VCF file 2 0.10 % No
similar to the 2 0.10 % No
FILTER INFO FORMAT 2 0.10 % No
the variant record 2 0.10 % No
QUAL FILTER INFO 2 0.10 % No
ALT QUAL FILTER 2 0.10 % No
to be ignored 2 0.10 % No
ID REF ALT 2 0.10 % No
contain “Alt” alleles 2 0.10 % No
CHROM POS ID 2 0.10 % No

SEO Keywords (Four Word)

Keyword Occurrence Density Possible Spam
from 1000 Genome Project 3 0.15 % No
equivalent representation in ADAMAvro 3 0.15 % No
QUAL FILTER INFO FORMAT 2 0.10 % No
points Birds of classes 2 0.10 % No
in ADAMAvro for a 2 0.10 % No
ADAMAvro for a Triallelic 2 0.10 % No
for a Triallelic site 2 0.10 % No
Birds of classes feathers 2 0.10 % No
— Data points Birds 2 0.10 % No
Data points Birds of 2 0.10 % No
to its equivalent representation 2 0.10 % No
Analysis — Data points 2 0.10 % No
Cluster Analysis — Data 2 0.10 % No
Format — Digging Deeper 2 0.10 % No
ADAM Format — Digging 2 0.10 % No
Genomics ADAM Format — 2 0.10 % No
its equivalent representation in 2 0.10 % No
representation in ADAMAvro for 2 0.10 % No
Format to its equivalent 2 0.10 % No
case we see that 2 0.10 % No

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About Priyanka Dangi
About Priyanka Dangi – MyGenomics
Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib
Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib – MyGenomics
Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together….
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Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site
Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics
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Genomics & ADAM Format — Digging Deeper – MyGenomics
Applying ADAM to process VCF Files from 1000 Genome Project
Applying ADAM to process VCF Files from 1000 Genome Project – MyGenomics

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Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics Skip to content MyGenomics Cloud Scale Genomic Analytics Home Technology Blog ContactWell-nighPriyanka Dangi Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site Posted on June 10, 2016January 23, 2017 pdangiPosted in ADAM VCF stands for VariantUndeniabilityFormat. VCF files help represent single wiring pair differences, or polymorphisms (SNPs) and other components of variation like insertions and deletions (INDELs), varying a number of gene repeats (copy number variations, or CNVs) and transposable elements. It is important to note that people are 99.9% genetically similar (about one SNP per 1000 bases). Existing formats used, for genetic data such as General full-length format (GFF) store all of the genetic data, much of which is verbose and redundant considering 99.9% of is the same and shared wideness the genomes. VCF stores only the variations slantingly with a reference genome. This blog only looks at that speciality of VCF file that deals with how the genotype and other sample-level information is represented. In my next blog, that talks well-nigh using K-Means|| clustering, we feed these specific fields of the VCF file ( an example of encoding of GT) to KMeans.train (more on this later) to cluster some of the pedigree samples from 1000 Genome Project. A triallelic site is a specific locus in a genome that contains three observed alleles counting the reference as one[Ref: G, Alt: A, C]. This would permit two or increasingly variant alleles. Shown unelevated is what you would undeniability a triallelic site where, wideness multiple samples in a cohort, you see vestige for two or increasingly non-reference alleles.   #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT HG00096 HG00097 HG00098 HG00099 1 155205492 VG01S1186 G A,C . PASS AC=0,4264;AF=0.00,1.00;AN=4264;set=broad GT 2/2 0/0 0/2 1/2 True multi-allelic sites are not commonly observed unless you squint at very large cohorts.     In ADAM framework, of all the schemas, the variant and genotype schemas present a larger throw-away from the representation used by the VariantUndeniabilityFormat (VCF). The most noticeable difference is that ADAM’s Avro schema representations have migrated yonder from VCF’s variant oriented representation to a matrix representation. Instead of the variant record serving to group together genotypes, the variant record is now embedded within the genotype itself as was shown in my older blog. Thus, a record represents the genotype prescribed to a sample, as opposed to a VCF row, where all cohorts are placid together. The second major modification, as seen below, is to unchangingly seem a biallelic representation. This differs from VCF, which allows multiallelic records. If a site contains a multiallelic variant (e.g., in VCF parlance this could be a 2/2 or 1/2 genotype), vcf2adam utility splits the variant into two or increasingly biallelic records. The sufficient statistics for each allele are then computed under a reference model similar to the model used in genome VCFs. If the sample does contain a multiallelic variant at the given site, this multiallelic variant is represented by referencing to flipside record via the OtherAlt enumeration. In essence, VCF conversion splits, multi-allelic sites into multiple single-alternate recrods and for samples whose genotype is a heterozygous mix of the ALT alleles, as shown below: scala> val genotypes:RDD[Genotype] = sc.loadGenotypes("/adam2").rdd scala> genotypes.filter(x => (x.getStart >= 155205490 && x.getSampleId=="HG00096" && x.getStart <= 155205493)) res21: org.apache.spark.rdd.RDD[org.bdgenomics.formats.avro.Genotype] = MapPartitionsRDD[263] at filter at :50 scala> res21.collect.foreach(println) [ { "variant": { "variantErrorProbability": null, "contigName": null, "start": null, "end": null, "referenceAllele": "G", "alternateAllele": "A", "svAllele": null, "isSomatic": false }, "contigName": "1", "start": 155205491, "end": 155205492, "variantCallingAnnotations": { "variantIsPassing": true, "variantFilters": [], "downsampled": null, "baseQRankSum": null, "fisherStrandBiasPValue": null, "rmsMapQ": null, "mapq0Reads": null, "mqRankSum": null, "readPositionRankSum": null, "genotypePriors": [], "genotypePosteriors": [], "vqslod": null, "culprit": null, "attributes": {} }, "sampleId": "HG00096", "sampleDescription": null, "processingDescription": null, "alleles": [ "OtherAlt", "OtherAlt" ], "expectedAlleleDosage": null, "referenceReadDepth": null, "alternateReadDepth": null, "readDepth": null, "minReadDepth": null, "genotypeQuality": null, "genotypeLikelihoods": [], "nonReferenceLikelihoods": [], "strandBiasComponents": [], "splitFromMultiAllelic": true, "isPhased": true, "phaseSetId": null, "phaseQuality": null }, { "variant": { "variantErrorProbability": null, "contigName": null, "start": null, "end": null, "referenceAllele": "G", "alternateAllele": "C", "svAllele": null, "isSomatic": false }, "contigName": "1", "start": 155205491, "end": 155205492, "variantCallingAnnotations": { "variantIsPassing": true, "variantFilters": [], "downsampled": null, "baseQRankSum": null, "fisherStrandBiasPValue": null, "rmsMapQ": null, "mapq0Reads": null, "mqRankSum": null, "readPositionRankSum": null, "genotypePriors": [], "genotypePosteriors": [], "vqslod": null, "culprit": null, "attributes": {} }, "sampleId": "HG00096", "sampleDescription": null, "processingDescription": null, "alleles": [ "Alt", "Alt" ], "expectedAlleleDosage": null, "referenceReadDepth": null, "alternateReadDepth": null, "readDepth": null, "minReadDepth": null, "genotypeQuality": null, "genotypeLikelihoods": [], "nonReferenceLikelihoods": [], "strandBiasComponents": [], "splitFromMultiAllelic": true, "isPhased": true, "phaseSetId": null, "phaseQuality": null } ]Consideringthis site is triallelic, results in AVRO schema format with 2 variant records for sample HG00096 at this site. In this case, we see that one genotypes contain alleles tabbed OtherAlt. This has to be ignored. The other genotypes contain “Alt” alleles resulting in C/C Homozygous Alt. Here is flipside example for sample HG00107.Unelevatedis a partial pericope from the VCF file. #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT HG00107 5 71737880 rs17378693 T A,C . PASS AC=593,3689;AF=0.138,0.862;AN=4282;set=broad GT 1/2   It’s equivalent representation in ADAM/Avro, found by filtering the Genotype RDD on sample and start/end position similar to the whilom example. [{ "variant": { "variantErrorProbability": null, "contigName": null, "start": null, "end": null, "referenceAllele": "T", "alternateAllele": "A", "svAllele": null, "isSomatic": false }, "contigName": "5", "start": 71737879, "end": 71737880, "variantCallingAnnotations": { "variantIsPassing": true, "variantFilters": [], "downsampled": null, "baseQRankSum": null, "fisherStrandBiasPValue": null, "rmsMapQ": null, "mapq0Reads": null, "mqRankSum": null, "readPositionRankSum": null, "genotypePriors": [], "genotypePosteriors": [], "vqslod": null, "culprit": null, "attributes": {} }, "sampleId": "HG00107", "sampleDescription": null, "processingDescription": null, "alleles": ["Alt", "OtherAlt"], "expectedAlleleDosage": null, "referenceReadDepth": null, "alternateReadDepth": null, "readDepth": null, "minReadDepth": null, "genotypeQuality": null, "genotypeLikelihoods": [], "nonReferenceLikelihoods": [], "strandBiasComponents": [], "splitFromMultiAllelic": true, "isPhased": true, "phaseSetId": null, "phaseQuality": null }, { "variant": { "variantErrorProbability": null, "contigName": null, "start": null, "end": null, "referenceAllele": "T", "alternateAllele": "C", "svAllele": null, "isSomatic": false }, "contigName": "5", "start": 71737879, "end": 71737880, "variantCallingAnnotations": { "variantIsPassing": true, "variantFilters": [], "downsampled": null, "baseQRankSum": null, "fisherStrandBiasPValue": null, "rmsMapQ": null, "mapq0Reads": null, "mqRankSum": null, "readPositionRankSum": null, "genotypePriors": [], "genotypePosteriors": [], "vqslod": null, "culprit": null, "attributes": {} }, "sampleId": "HG00107", "sampleDescription": null, "processingDescription": null, "alleles": ["OtherAlt", "Alt"], "expectedAlleleDosage": null, "referenceReadDepth": null, "alternateReadDepth": null, "readDepth": null, "minReadDepth": null, "genotypeQuality": null, "genotypeLikelihoods": [], "nonReferenceLikelihoods": [], "strandBiasComponents": [], "splitFromMultiAllelic": true, "isPhased": true, "phaseSetId": null, "phaseQuality": null }] In this case, we see that both genotypes contain alleles tabbed OtherAlt. These are to be ignored. Both genotypes moreover contain “Alt” alleles. These are gotten from the associated variant records, and in this specimen the Alt alleles are different. Thus, this individual gets A and C (Hetero-Alt) References: 1. http://gatkforums.broadinstitute.org/gatk/discussion/6455/biallelic-vs-multiallelic-sites 2. http://digitalassets.lib.berkeley.edu/techreports/ucb/text/EECS-2015-65.pdf 3. https://wegetsignal.wordpress.com/2015/09/30/big-data-genomics-avro-schema-representation-of-biallelic-multi-allelic-sites-from-vcf/ 4. VCF Format Specifications ADAM, Avro, VCF Post navigation Genomics & ADAM Format — Digging DeeperCluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. Leave a Reply Cancel reply Your email write will not be published. Required fields are marked *Comment Name * Email * Website Search for: Recent Posts Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site Genomics & ADAM Format — Digging Deeper Applying ADAM to process VCF Files from 1000 Genome Project