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

doi:10.1093/bioinformatics/btu401

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

Fondazione Don Carlo Gnocchi Onlus

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	2852-2859
Number of pages	8
Journal	Bioinformatics
Volume	30
Issue number	20
DOIs	https://doi.org/10.1093/bioinformatics/btu401
Publication status	Published - Oct 15 2014

ASJC Scopus subject areas

Medicine(all)

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10.1093/bioinformatics/btu401

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H3M2 : detection of runs of homozygosity from whole-exome sequencing data. / Magi, Alberto; Tattini, Lorenzo; Palombo, Flavia; Benelli, Matteo; Gialluisi, Alessandro; Giusti, Betti; Abbate, Rosanna; Seri, Marco; Gensini, Gian F ranco; Romeo, Giovanni; Pippucci, Tommaso.

In: Bioinformatics, Vol. 30, No. 20, 15.10.2014, p. 2852-2859.

Research output: Contribution to journal › Article › peer-review

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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.comSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.",

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AU - Gialluisi, Alessandro

AU - Giusti, Betti

AU - Abbate, Rosanna

AU - Seri, Marco

AU - Gensini, Gian F ranco

AU - Romeo, Giovanni

AU - Pippucci, Tommaso

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N2 - 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.comSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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

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