H3M2: Detection of runs of homozygosity from whole-exome sequencing data

Runs of homozygosity (ROH) can be defined as sizable chromo- somal stretches of homozygous genotypes, ranging in length from tens of kilobases to megabases. ROHs can be relevant for popu- lation and medical genetics, playing a role in predisposition to both rare and common disorders. ROHs are commonly detected by SNP microarrays, but attempts have been made to use Whole Exome Sequencing (WES) data. Currently available methods devel- oped for the analysis of uniformly spaced SNP-array maps do not fit easily the sparse and non uniform distribution of the WES tar- get design. To meet the need of an approach specifically tailored to WES data we developed H3M2, an original algorithm based on Het- erogeneous Hidden Markov Model that incorporates inter-marker distances to detect ROH from Whole Exome Sequencing (WES) data. We evaluated the performance of H3M2 to correctly identify ROHs on synthetic chromosomes and examined its accuracy in detecting ROHs of different length (short, medium and long) from real 1000 genomes project data. H3M2 turned out to be more accurate than GERMLINE and PLINK, two state-of-the-art algorithms, especially in the detection of short and medium ROHs. H3M2 is freely available at https://sourceforge.net/projects/h3m2/.