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HiCdat: a fast and easy-to-use Hi-C data analysis tool


Schmid, Marc W; Grob, Stefan; Grossniklaus, Ueli (2015). HiCdat: a fast and easy-to-use Hi-C data analysis tool. BMC Bioinformatics, 16:277.

Abstract

BACKGROUND The study of nuclear architecture using Chromosome Conformation Capture (3C) technologies is a novel frontier in biology. With further reduction in sequencing costs, the potential of Hi-C in describing nuclear architecture as a phenotype is only about to unfold. To use Hi-C for phenotypic comparisons among different cell types, conditions, or genetic backgrounds, Hi-C data processing needs to be more accessible to biologists. RESULTS HiCdat provides a simple graphical user interface for data pre-processing and a collection of higher-level data analysis tools implemented in R. Data pre-processing also supports a wide range of additional data types required for in-depth analysis of the Hi-C data (e.g. RNA-Seq, ChIP-Seq, and BS-Seq). CONCLUSIONS HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.

Abstract

BACKGROUND The study of nuclear architecture using Chromosome Conformation Capture (3C) technologies is a novel frontier in biology. With further reduction in sequencing costs, the potential of Hi-C in describing nuclear architecture as a phenotype is only about to unfold. To use Hi-C for phenotypic comparisons among different cell types, conditions, or genetic backgrounds, Hi-C data processing needs to be more accessible to biologists. RESULTS HiCdat provides a simple graphical user interface for data pre-processing and a collection of higher-level data analysis tools implemented in R. Data pre-processing also supports a wide range of additional data types required for in-depth analysis of the Hi-C data (e.g. RNA-Seq, ChIP-Seq, and BS-Seq). CONCLUSIONS HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.

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Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Plant and Microbial Biology
07 Faculty of Science > Zurich-Basel Plant Science Center
Dewey Decimal Classification:580 Plants (Botany)
Language:English
Date:2015
Deposited On:12 Jan 2016 15:37
Last Modified:08 Dec 2017 16:42
Publisher:BioMed Central
ISSN:1471-2105
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s12859-015-0678-x
PubMed ID:26334796

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