Variant Analysis IntroductionDeanna M. Church Staff Scientist, NCBI

@deannachurch Short Course in Medical Genetics 2013

sequences alignments genotype likelihoods individual variants1

10

100

1,000

10,000

100,000

size

(gig

abyt

es)

component

1092 genomes (low coverage + exome)

38.2M SNPs3.9M Short Indels and14K Deletions

FASTQBAM

VCF

VCF

FASTQBAM

VCF

VCF

Steve Sherry, NCBI

http://www.bioplanet.com/gcat

http://www.ncbi.nlm.nih.gov/variation/tools/1000genomes

Variation Databases

http://www.ncbi.nlm.nih.gov/snp

Collection of small nucleotide variation (SNVs) Typically <50 bpSome are polymorphicSome are rareSome are errorsSubmissions clustered to make reference variants (rsIDs)

Variation Databases

Blue variants are all T insertionsSubmitters submit in different part of the polyT tractNeed additional analysis to cluster these

Variation Databases

Collection of large-scale variationBreakpoint ambiguityComplex variants (chromothripsis)Challenging to compare variants from different methodsNo reference variants (yet)

http://www.ncbi.nlm.nih.gov/dbvar

Variant Call Ambiguitystart stop

Inner start Inner stop

Outer start Outer stop

Probes with decreased signal intensityProbes with expected signal intensity

breakpoint breakpoint

Inner start Inner stop

Variant Call AmbiguityOuter start Outer stop

Fosmid clone (40 Kb +/- 1 Kb)

20Kb Clone has an insertionrelative to the genome

Clone has a deletionrelative to the genome 60 Kb

Variation Databases

http://www.ncbi.nlm.nih.gov/clinvar

How confident am I that my variant call is correct?

http://www.bioplanet.com/gcat

Fonseca et al., 2012

Available NGS Alignersalready out of data

http://www.bioplanet.com/gcat

Alignment Test

Align back to the source

Simulated ReadsGood: know where the reads goNot so good: hard to simulate real data

http://www.bioplanet.com/gcat

Variant Calling Test

Variant Calling TestTransition /Transversion ratio (Ti/Tv)

A C

GTTransversions

Transitions

Random: 0.5Whole Genome: 2.0 – 2.1Exome: 3-3.5

Variant Calling Test

Note: Difficult to test variant calling independentlyfrom the aligner as they are often coupled.

Variant Calling Test

Benchmarking on known samples

NA12878NA19240

http://www.ncbi.nlm.nih.gov/variation/tools/get-rm

Calls

Tests

cSRA

ConcordantDiscordantNA

Target audience: Clinical testing labsSubmissions from: Clinical and Research labs

https://main.g2.bx.psu.edu/

Variant Analysis Pipelines: Galaxy

Variant Analysis Pipelines: GalaxyWorkflows

Save themShare them

Can run on Amazon Cloud Large community

Reproducibility

Annotating Variants

NC_000001.10:g.170508656G>T

NC_000001.10:g.170508561T>A

NC_000001.10:g.170508573T>C

NC_000001.10:g.170508724T>C

Annotating VariantsMolecular Consequences (often predicted)

Damaging amino acid changeAffect a splice siteChange a regulatory feature

Functional Consequences (typically asserted)

Experiments show the change affects expressionAllele associated with a disorderAllele shown to affect some function

Annotating Variants

MAPKAPK2DYRK3

Annotating Variants

http://www.ensembl.org/info/docs/variation/vep/index.html

Upload your list of variants, get back Is the variant known?Is the variant predicted to be deleterious to a protein (SIFT, PolyPhen)Overlap with predicted regulatory regionHGVS expressions

http://www.ncbi.nlm.nih.gov/variation/tools/reporter

Annotating Variants

Upload your list of variants, get back Is the variant known?Does the allele have a molecular consequence (change AA, nonsynonymous)HGVS expressionsClinVar informationAvailable Genetic TestsPublications

Take home messages

Lots of methods for sequence alignmentLots of methods for variant calling

Typically developed to use a particular alignerDifferent data sources can affect your annotation