Existing software for checking relatedness requires jointly-called germ-line variant calls, but cancer projects have only somatic calls between tumor-normal pairs.
somalier makes checking any number of samples for identity easy directly from the alignments:
somalier --threads 4 --sites sites.vcf.gz -f:/data/human/g1k_v37_decoy.fa *.cram
where sites is a VCF of variant sites (provided by somalier for hg19). The interactive output that's produced (similar to peddy) makes it fast and easy to detect mismatched samples and sample-swaps.
Optional arguments let the user specify expected groups of samples or a ped/fam file indicating family relationships.
--sites is a VCF of known polymorphic sites in VCF format. A good set is provided in
the releases but any set of common variants will work.
get a binary from here
somalier requires libhts.so from htslib to be in
a standard location or indicated with the LD_LIBRARY_PATH environment variable.
Users can also get a docker image here which contains htslib and a somalier binary ready-for-use.
somalier [options] <bam/cram/list>...
Arguments:
<bam/cram> file(s) for samples of interest. or a `list` with lines of bam,index paths.
Options:
-s --sites <vcf> vcf file with lines of sites to use for relatedness estimation.
-t --threads <int> optional number of processors to use for parallelization.
-d --min-depth <int> only consider sites with at least this depth [default: 7].
-f --fasta <reference> path to reference fasta file.
-g --groups <path> optional path to expected groups of samples (e.g. tumor normal pairs).
specified as comma-separated groups per line e.g.:
normal1,tumor1a,tumor1b
normal2,tumor2a
-p --ped <path> optional path to a ped/fam file indicating the expected relationships
among samples.
-o --output <prefix> output prefix for results.
somalier takes a list of known sites. Even a few hundred (or dozen) sites can be a very
good indicator of relatedness. The best sites are those with a population allele frequency
close to 0.5 as that maximizes the probability that any 2 samples will differ.
A list of such sites is provided in the releases
for GRCh37.
In order to quickly calculate genotypes at these sites, somalier assays the exact base
without using pileup. It also parallelizes across
samples with as many threads as requested. In addition, it uses hts-nim
which is a very fast wrapper of htslib.
For each sample-pair, it reports:
- IBS0 -- the number of sites where one sample is hom-ref and another is hom-alt
- IBS2 -- the number of sites where the samples have the same genotype
- shared-hets -- the number of sites where both samples are heterozygotes
- shared-hom-alts -- the number of sites where both samples are homozygous alternate
These are used to calculate relatedness and a measure of relatedness that is unaffected by loss-of-heterozygosity that is often seen in some cancers. The interactive output allows toggling between any of these measures.
It also reports depth information and the count of HET, HOM_REF, HOM_ALT, and unknown genotypes for each sample
along with a number of metrics that are useful for general QC.
Here, each point is a pair of samples. We can see that the expected identical sample-pairs (e.g. tumor-normal pairs) specified by the user and drawn in red mostly cluster together on the right. Unrelateds cluster on the lower left. The sample-swaps are the blue points that cluster with the red. In the somalier output, the user can hover to see which sample-pairs are involved each point
somalier is free and unrestricted for non-commercial use. For commercial use, please contact [[email protected]]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499645/
https://academic.oup.com/bioinformatics/article/33/4/596/2624551
This work was motivated by interaction and discussions with Preeti Aahir and several early users who provided valuable feedback.