Publication Date:
2014-10-04
Description:
Motivation: Runs of homozygosity (ROH) are sizable chromosomal stretches of homozygous genotypes, ranging in length from tens of kilobases to megabases. ROHs can be relevant for population and medical genetics, playing a role in predisposition to both rare and common disorders. ROHs are commonly detected by single nucleotide polymorphism (SNP) microarrays, but attempts have been made to use whole-exome sequencing (WES) data. Currently available methods developed for the analysis of uniformly spaced SNP-array maps do not fit easily to the analysis of the sparse and non-uniform distribution of the WES target design. Results: To meet the need of an approach specifically tailored to WES data, we developed $${H}^{3}{M}^{2}$$ , an original algorithm based on heterogeneous hidden Markov model that incorporates inter-marker distances to detect ROH from WES data. We evaluated the performance of $${H}^{3}{M}^{2}$$ 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. $${H}^{3}{M}^{2}$$ 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. Availability and implementation : $${H}^{3}{M}^{2}$$ is a collection of bash, R and Fortran scripts and codes and is freely available at https://sourceforge.net/projects/h3m2/ . Contact : albertomagi@gmail.com Supplementary information : Supplementary data are available at Bioinformatics online.
Print ISSN:
1367-4803
Electronic ISSN:
1460-2059
Topics:
Biology
,
Computer Science
,
Medicine
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