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

Alberto Magi, Lorenzo Tattini, Flavia Palombo, Matteo Benelli, Alessandro Gialluisi, Betti Giusti, Rosanna Abbate, Marco Seri, Gian F ranco Gensini, Giovanni Romeo, Tommaso Pippucci

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Abstract

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 [Formula: see text], 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 [Formula: see text] 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. [Formula: see text] 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: [Formula: see text] 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.

Original languageEnglish
Pages (from-to)2852-2859
Number of pages8
JournalBioinformatics
Volume30
Issue number20
DOIs
Publication statusPublished - Oct 15 2014

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ASJC Scopus subject areas

  • Medicine(all)

Cite this

Magi, A., Tattini, L., Palombo, F., Benelli, M., Gialluisi, A., Giusti, B., Abbate, R., Seri, M., Gensini, G. F. R., Romeo, G., & Pippucci, T. (2014). H3M2: detection of runs of homozygosity from whole-exome sequencing data. Bioinformatics, 30(20), 2852-2859. https://doi.org/10.1093/bioinformatics/btu401