Abstract
MotivationGenome 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.ResultsWe 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 optimize 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 and implementationGAMIBHEAR is available as an R package under the open-source GPL-2 license at https://bitbucket.org/schwarzlab/gamibhear.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Genome Architecture Mapping (GAM) is a novel digestion- and ligation-free experimental technique for assessing the 3D chromatin structure from sequencing a collection of thin cryosectioned nuclear profiles (NuPs) (Beagrie et al, 2017)
We report the total proportion of phased heterozygous single nucleotide variants (SNVs) next to the standard S50 (Lo et al, 2011), N50 (Lander et al, 2001) and adjusted N50 (AN50; Lo et al, 2011) metrics which give an impression of the median size and span of the reconstructed haplotype blocks
Using the novel GAM method, 1281 single NuPs were generated from the F123 mouse embryonic stem cell (mESC) cell line, out of which 1123 passed quality control(unique 4DN identifiers provided in Supplementary Data)
Summary
Genome Architecture Mapping (GAM) is a novel digestion- and ligation-free experimental technique for assessing the 3D chromatin structure from sequencing a collection of thin cryosectioned nuclear profiles (NuPs) (Beagrie et al, 2017). One advantage of GAM over competing methods, such as Hi-C (Lieberman-Aiden et al, 2009), is that GAM only requires several hundreds of cells to obtain high-resolution contact maps (Kempfer and Pombo, 2019; Beagrie et al, 2020; Fiorillo et al, 2020). This makes GAM useful for the study of chromatin contacts in rare biological materials, such as human biopsies. Methods, variants of the Minimum Error Correction (MEC) problem are used with varying error distributions and insert lengths (Bansal and Bafna, 2008). The MEC problem is computationally hard under a variety of
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