multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.
|Author||John Stansfield <firstname.lastname@example.org>, Mikhail Dozmorov <email@example.com>|
|Bioconductor views||HiC Normalization Sequencing Software|
|Maintainer||John Stansfield <firstname.lastname@example.org>, Mikhail Dozmorov <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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