Analysis methods for studying the 3D architecture of the genome

Genome Biology
Ferhat Ay, William S Noble

Abstract

The rapidly increasing quantity of genome-wide chromosome conformation capture data presents great opportunities and challenges in the computational modeling and interpretation of the three-dimensional genome. In particular, with recent trends towards higher-resolution high-throughput chromosome conformation capture (Hi-C) data, the diversity and complexity of biological hypotheses that can be tested necessitates rigorous computational and statistical methods as well as scalable pipelines to interpret these datasets. Here we review computational tools to interpret Hi-C data, including pipelines for mapping, filtering, and normalization, and methods for confidence estimation, domain calling, visualization, and three-dimensional modeling.

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Citations

Feb 16, 2016·Genomics, Proteomics & Bioinformatics·Vijay RamaniZhijun Duan
Dec 15, 2015·Journal of Proteome Research·Chris BielowStefan Kempa
Sep 1, 2015·Genome Biology·David M Gilbert, Peter Fraser
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Mar 21, 2019·Genome Biology·Galip Gürkan YardımcıWilliam S Noble
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Feb 6, 2017·Genome Biology·Galip Gürkan Yardımcı, William Stafford Noble
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Datasets Mentioned

BETA
GM12878

Methods Mentioned

BETA
Hi-C
PCR
ICE
human
MDS
single-cell Hi-C

Software Mentioned

HiCUP
HIPPIE
Hiclib
Hi
Bowtie
Fit
STAR
WashU Epigenome Browser
Box
Subread

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