Analyses of Indels

Motivation

This wiki page details some standard Indel analyses which hopefully can help the group in understanding the issues and perform the analyses quickly without reinventing the wheel.

Tools

You can download vt and have some working knowledge of PERL to do stuff that vt does not support.

Analyses

Normalization

Indel representation is not unique, you should normalize them and remove duplicates.

The following table shows the number of variants that had to be normalized and the corresponding type of normalization performed and the ensuing number of duplicate variants found for some of the 1000 Genomes Trio High Coverage call sets. Although left alignment seems to be a trivial concept, it is easily overlooked and remain a common mistake. Another example is the Mills et al. data set which followed up with 10004 Indels for validation. Out of 9996 passed variants, it was found that after normalization, only 8904 distinct Indels remain - about a loss of 11% of variant thought distinct.

  Variant normalization is implemented in vt and this page explains the algorithm 
  and also provides a simple proof of correctness - Variant Normalization

Dataset	Freebayes	Haplotyecaller	PINDEL	Platypus	RTG	Samtools	SGA
Biallelic
Left trim	27069	1	0	0	0	0	15047
Left aligned	3	1	1	0	12262	2	1892
Multi-allelic
Left trim	40782	0	0	0	374
Left aligned	1892	0	0	0	1329	1	0
Right trimmed	0	0	0	25393	0	11	0
Duplicate variants	0	1	155	3143	286	8	7541

Coding regions

The proportion of frameshift Indels amongst coding region indels is a potential indicator of quality.

STR

Annotation of STRs is really important. Show example of a deceptive single base pair variant

Concordance

Can check concordance of genotypes between callers

Overlapping percentages with known data sets

With Mills with dbSNP with exome chips with genotyping chips if available

Useful stratifying features

AF - rare versus common Indel length - computed naively versus tract length Allele frequency bins Type of Indels - homopolymer types and STR types and isolated Adjacent SNPs Adjacent MNPs Clumping variants

Other useful evaluations

genotype likelihood concordance concordance stratified by indel length or tract length mendelian concordance by tract length