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Bioinformatics. 2021 Apr 08; doi: 10.1093/bioinformatics/btab238. Epub 2021 Apr 08.

GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data.

Bioinformatics (Oxford, England)

Julia Markowski, Rieke Kempfer, Alexander Kukalev, Ibai Irastorza-Azcarate, Gesa Loof, Birte Kehr, Ana Pombo, Sven Rahmann, Roland F Schwarz

Affiliations

  1. Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Hannoversche Str. 28, 10115 Berlin, Germany.
  2. Department of Biology, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany.
  3. Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Str. 2, 10178 Berlin, Germany.
  4. Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
  5. Genome Informatics, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, 45122 Essen, Germany.

PMID: 33830196 PMCID: PMC8504635 DOI: 10.1093/bioinformatics/btab238

Abstract

MOTIVATION: Genome Architecture Mapping (GAM) was recently introduced as a digestion- and ligation-free method to detect chromatin conformation. Orthogonal to existing approaches based on chromatin conformation capture (3C), GAM's ability to capture both inter- and intra-chromosomal contacts from low amounts of input data makes it particularly well suited for allele-specific analyses in a clinical setting. Allele-specific analyses are powerful tools to investigate the effects of genetic variants on many cellular phenotypes including chromatin conformation, but require the haplotypes of the individuals under study to be known a-priori. So far however, no algorithm exists for haplotype reconstruction and phasing of genetic variants from GAM data, hindering the allele-specific analysis of chromatin contact points in non-model organisms or individuals with unknown haplotypes.

RESULTS: We present GAMIBHEAR, a tool for accurate haplotype reconstruction from GAM data. GAMIBHEAR aggregates allelic co-observation frequencies from GAM data and employs a GAM-specific probabilistic model of haplotype capture to optimise phasing accuracy. Using a hybrid mouse embryonic stem cell line with known haplotype structure as a benchmark dataset, we assess correctness and completeness of the reconstructed haplotypes, and demonstrate the power of GAMIBHEAR to infer accurate genome-wide haplotypes from GAM data.

AVAILABILITY: GAMIBHEAR is available as an R package under the open source GPL-2 license at https://bitbucket.org/schwarzlab/gamibhear.

MAINTAINER: [email protected].

SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

© The Author(s) 2021. Published by Oxford University Press.

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