Towards a unified theory of variant calling

Johannes Köster, Louis Dijkstra, Tobias Marschall, Alexander Schönhuth

 

Genome Informatics 2020

small

structural

SNVs, Indels

Inversions, Duplications, Indels, ...

?

?

?

?

somatic

germline

Variant calling

small

structural

?

?

somatic

germline

Variant calling

tumor/normal

sample, cohort, pedigree

?

?

small

structural

germline

somatic

GATK

Freebayes

Platypus

Pindel

Mutect

Strelka

Octopus

Lancet

Variant calling

Delly

Manta

Gridss

##fileformat=VCFv4.3
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM POS      ID         REF   ALT    QUAL  FILTER   INFO                             FORMAT       NA00001  
20     14370    rs6054257  G     A      29    PASS    NS=3;DP=14;AF=0.5;DB;H2           GT:GQ:DP:HQ  0|0:48:1:51,51 
20     17330    .          T     A      3     q10     NS=3;DP=11;AF=0.017               GT:GQ:DP:HQ  0|0:49:3:58,50 
20     1110696  rs6040355  A     G,T    67    PASS    NS=2;DP=10;AF=0.333,0.667;AA=T;DB GT:GQ:DP:HQ  1|2:21:6:23,27 
20     1230237  .          T     .      47    PASS    NS=3;DP=13;AA=T                   GT:GQ:DP:HQ  0|0:54:7:56,60 
20     1234567  microsat1  GTC   G,GTCT 50    PASS    NS=3;DP=9;AA=G                    GT:GQ:DP     0/1:35:4       
##fileformat=VCFv4.3
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM POS      ID         REF   ALT    QUAL  FILTER   INFO                             FORMAT       NA00002          NA00003
20     14370    rs6054257  G     A      29    PASS    NS=3;DP=14;AF=0.5;DB;H2           GT:GQ:DP:HQ  1|0:48:8:51,51   1/1:43:5:.,.
20     17330    .          T     A      3     q10     NS=3;DP=11;AF=0.017               GT:GQ:DP:HQ  0|1:3:5:65,3     0/0:41:3
20     1110696  rs6040355  A     G,T    67    PASS    NS=2;DP=10;AF=0.333,0.667;AA=T;DB GT:GQ:DP:HQ  2|1:2:0:18,2     2/2:35:4
20     1230237  .          T     .      47    PASS    NS=3;DP=13;AA=T                   GT:GQ:DP:HQ  0|0:48:4:51,51   0/0:61:2
20     1234567  microsat1  GTC   G,GTCT 50    PASS    NS=3;DP=9;AA=G                    GT:GQ:DP     0/2:17:2         1/1:40:3

⊖

Problem:

accumulation of errors

More complex: so far...

small

structural

germline

somatic

Delly

GATK

Freebayes

Platypus

Pindel

Mutect

Strelka

Lancet

Manta

Octopus

arbitrary

Gridss

Approach

Given:

  • aligned NGS reads
  • candidate variants

Find:

  • classification of variants into events (somatic, germline, ...)
  • unbiased allele frequency estimates
  • while controlling FDR

Model

sample a

sample b

...

contaminates

Model

  • insert size
  • read sequence
  • strand
  • read orientation

Latent variables:

  • allele frequency
  • fragment from variant allele
  • fragment correctly mapped
  • biases

Observed variables:

Model

\(\xi_i \sim \text{Bernoulli}(\alpha \theta_c \tau + (1-\alpha) \theta_h \tau)\)

\(\omega_i \sim Bernoulli(\pi_i)\)

\(Z_i \mid \xi_i, \omega_i=1,\beta,\delta \sim\)

\(\beta, \delta\)

  • allele frequency
  • contamination
  • sampling bias
  • typing uncertainty
  • strand bias, read orientation bias
  • mapping uncertainty

Model

\(\Pr(Z_i \mid \theta_c,\theta_h,\beta) =\)

⊕ Bayes' theorem

= posterior probability for events

Bayesian FDR control

Variant calling grammar

samples:
  janedoe:
    universe: "0.0 | 0.5 | 1.0"
events:
  present: "janedoe:0.5 | janedoe:1.0"
samples:
  normal:
    resolution: 5
    universe: "0.0 | 0.5 | 1.0 | ]0.0,0.5["
  tumor:
    resolution: 100
    universe: "[0.0,1.0]"
    contamination:
      by: normal
      fraction: 0.25
events:
  germline:        "normal:0.5 | normal:1.0"
  somatic_normal:  "normal:]0.0,0.5["
  somatic_tumor:   "normal:0.0 & tumor:]0.0,1.0]"

Variant calling grammar

samples:
  normal:
    resolution: 5
    universe: "0.0 | 0.5 | 1.0 | ]0.0,0.5["
  tumor:
    resolution: 100
    universe: "[0.0,1.0]"
    contamination:
      by: normal
      fraction: 0.25
  relapse:
    resolution: 100
    universe: "[0.0,1.0]"
    contamination:
      by: normal
      fraction: 0.53
events:
  germline:        "normal:0.5 | normal:1.0"
  somatic_normal:  "normal:]0.0,0.5["
  somatic_tumor:   "normal:0.0 & tumor:]0.0,1.0]"
  somatic_relapse: "normal:0.0 & tumor:0.0 & relapse:]0.0,1.0]"

Variant calling grammar

samples:
  romeo:
    universe:
      all: "0.0 | 0.5 | 1.0"
      X: "0.0 | 1.0"
      Y: "0.0 | 1.0"
  juliet:
    universe:
      all: "0.0 | 0.5 | 1.0"
      Y:   "0.0"

events:
  both_het:    "juliet:0.5 & romeo:0.5"
  both_hom:    "juliet:1.0 & romeo:1.0"
  juliet_only: "(juliet:0.5 | juliet:1.0) & romeo:0.0"
  romeo_only:  "(romeo:0.5 | romeo:1.0) & juliet:0.0"

https://genetics.thetech.org

Variant calling grammar

White box model

chr1	1200	.	GAAGCCATCTGCCCCATGGGAAAGTGACTTAAT	G	.	.	
  SVLEN=-32;PROB_SOMATIC_TUMOR=0.110292;PROB_ABSENT=202.181;PROB_GERMLINE_HET=61.7704;
  PROB_SOMATIC_NORMAL=16.0075;PROB_GERMLINE_HOM=4346.23;PROB_ARTIFACT=103.395	
  DP:AF:OBS:SB:ROB	
  36:0:11Np+<10Np+>8Np-<7Np->:.:.	
  48:0.102431:14Np+<13Np-<11Np->8Np+>1Vp-<1Vp+>:.:.
  • posterior allele frequency estimate
  • observations (count, posterior odds, type, strand, read orientation)
  • strand bias estimate
  • read orientation estimate
  • event probabilities (PHRED scaled)

https://varlociraptor.github.io

Towards a unified theory of variant calling

By Johannes Köster

Towards a unified theory of variant calling

Talk at Genome Informatics 2020

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