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Aaron Quinlan University of Utah quinlanlab.org @aaronquinlan ! ! ! ! Making queries of the genome less difficult.

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...CCTCATGCATGGAAA... Genetic variation ...CCTCATGTATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGTATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGTATGGAAA... Variant prioritization requires context.

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...CCTCATGCATGGAAA... Genetic variation ...CCTCATGTATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGTATGGAAA... ...CCTCATGCATGGAAA... ...CCTCATGTATGGAAA... Chromatin marks DNA methylation RNA expression TF binding Variant prioritization requires context.

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• inconsistent chromosome labels. • different sorting criteria. • mixed UNIX/Windows newlines. • file violates spec with vigor. • program expects exact extension. • file is gzipp’ed, not bgzipp’ed. • annotations use diff. genome builds. • tool only works for one format. • tool is hard-coded for specific build. • tool requires act of gods to compile.

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vcfanno will annotate your VCF with panache. Naked VCF vcfanno   +   configuration   file VCF w/ annotations in INFO field Brent Pedersen https://github.com/brentp/vcfanno VCF, BED, GFF, BAM, (soon BW)

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file.

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file. Match on POS+REF+ALT for VCF annotations.

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file. Allows multiple annotations from each file Match on POS+REF+ALT for VCF annotations.

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file. Allows multiple annotations from each file Can rename the annotations in the resulting VCF Match on POS+REF+ALT for VCF annotations.

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file. Allows multiple annotations from each file Can rename the annotations in the resulting VCF Multiple operations to summarize the results of multiple hits in annot. file: mean,  max,  min   concat,  count,  uniq   first,  flag Match on POS+REF+ALT for VCF annotations.

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[[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"] vcfanno configuration file. Allows multiple annotations from each file Can rename the annotations in the resulting VCF Multiple operations to summarize the results of multiple hits in annot. file: mean,  max,  min   concat,  count,  uniq   first,  flag Match on POS+REF+ALT for VCF annotations. Javascript for custom computations. variance() defined in custom.js

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before and after vcfanno vcfanno AC=11;AF=0.017 AC=11;AF=0.017;   exac_aaf=0.0012;   exac_num_het=8;   rs_ids=1234;   gerp_mean=7.25e-­‐07   gerp_var=1.39e-­‐08 Naked VCF Dressed VCF [[annotation]]   file=“ExAC.v3.vcf”   fields=[“AF”,  “AC_Het”]   names=[“exac_aaf”,  “exac_num_het”]   ops=[“first”,  “first”]   ! [[annotation]]   file="dbsnp.b141.vcf.gz"   fields=["ID"]   names=["rs_ids"]   ops=[“concat"]   ! [[annotation]]   file="gerp.elements.bed.gz"   columns=[4,4]   names=[“gerp_mean”,”gerp_var”]   ops=[“mean”,  "js:variance(vals)"]

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New parallel “chromsweep”. vcfanno is speedy. 18 annotations: 29K variants / sec @ 12 cores See poster 160 for details

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Individual-centric queries with Genotype Query Tools (GQT) github.com/ryanlayer/gqt In press. Ryan Layer http://biorxiv.org/content/early/2015/04/20/018259

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A variant-centric query: Which variants affect BRCA1?

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bcftools  view  \   -­‐r  17:43044295-­‐43125483  \   1000g.vcf                                      OR   ! tabix  1000g.vcf  17:43044295-­‐43125483   ! Existing tools handle variant-centric queries well

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An individual-centric query: In which variants are all affected males heterozygous?

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In which variants are all affected males heterozygous?

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In which variants are all affected males heterozygous?

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Idea: transpose the genotype matrix G GT Note: other tricks included for speed/compression, please see manuscript

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In which variants are all affected males heterozygous?

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Affected males In which variants are all affected males heterozygous?

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In which variants are all affected males heterozygous?

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In which variants are all affected males heterozygous?

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Great, but what about indexing variant and genotype metadata?

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Bitmap indices of variant metadata (VEP consequence) VEP consequence bitmap: 1   0   0   0   0   0   0   …   0 synon. missense 0   0   0   0   0   0   1   …   0 stopgain 0   0   0   0   0   0   0   …   1 splice 0   0   0   0   1   0   0   …   0 .  .  .

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Bitmap indices of genotype metadata (depth) Ongoing: how to optimize lossiness of quantization?

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Bitmap indices of genotype metadata (depth) Genotype depth bitmap 1   0   0   0   0   0   0   …   0 0 1 0   1   0   0   0   0   0   …   0 2 0   0   0   0   0   0   1   …   0 3 0   0   0   1   0   0   0   …   0 10 0   0   0   0   0   0   0   …   1 20 0   0   0   0   0   1   0   …   0 25-30 0   0   0   0   1   0   0   …   0 >30 0   0   1   0   0   0   0   …   0 Ongoing: how to optimize lossiness of quantization?

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Future: A Genome Query Language? Variant-centric (bcftools, BGT) + = General Genome Query Language (based on discussions w/ Heng Li) VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in cases and rare in controls. b gqt query study.gqt study.db -p "phenotype == 2" -g "maf() > 0.05" -p "phenotype == 1" -g "maf() < 0.05" gqt -p -g b VCF In F V In VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in g Individual-centric (GQT, BGT) Individuals Variants Variants Individuals

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Future: A Genome Query Language? Variant-centric (bcftools, BGT) + = General Genome Query Language (based on discussions w/ Heng Li) VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in cases and rare in controls. b gqt query study.gqt study.db -p "phenotype == 2" -g "maf() > 0.05" -p "phenotype == 1" -g "maf() < 0.05" gqt -p -g b VCF In F V In VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in g Individual-centric (GQT, BGT) Individuals Variants Variants Individuals SELECT  *      VARIANT  gene="TP53"  AND  impact="HIGH"      SAMPLE  affected  IS  (ancestry="EA"                                                AND  phenotype=2                                              AND  BMI>35)      GENOTYPE  affected.MAF()>0.05

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Future: A Genome Query Language? Variant-centric (bcftools, BGT) + = General Genome Query Language (based on discussions w/ Heng Li) VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in cases and rare in controls. b gqt query study.gqt study.db -p "phenotype == 2" -g "maf() > 0.05" -p "phenotype == 1" -g "maf() < 0.05" gqt -p -g b VCF In F V In VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in g Individual-centric (GQT, BGT) Individuals Variants Variants Individuals SELECT  *      VARIANT  gene="TP53"  AND  impact="HIGH"      SAMPLE  affected  IS  (ancestry="EA"                                                AND  phenotype=2                                              AND  BMI>35)      GENOTYPE  affected.MAF()>0.05

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Future: A Genome Query Language? Variant-centric (bcftools, BGT) + = General Genome Query Language (based on discussions w/ Heng Li) VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in cases and rare in controls. b gqt query study.gqt study.db -p "phenotype == 2" -g "maf() > 0.05" -p "phenotype == 1" -g "maf() < 0.05" gqt -p -g b VCF In F V In VCF A B PED SQL database GQT index Individuals Variants 3 4 5 6 9 gqt convert ped gqt convert vcf D C Find variants that are common in g Individual-centric (GQT, BGT) Individuals Variants Variants Individuals SELECT  *      VARIANT  gene="TP53"  AND  impact="HIGH"      SAMPLE  affected  IS  (ancestry="EA"                                                AND  phenotype=2                                              AND  BMI>35)      GENOTYPE  affected.MAF()>0.05

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Thank you! Funding: Brent Pedersen Ryan Layer Jim Havrilla

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Students and Postdocs wanted. This could be you. Note: this is not me. [email protected]