Package: hicrep
Title: Measuring the reproducibility of Hi-C data
Version: 1.8.0
Authors@R: person("Tao", "Yang", email = "xadmyangt@gmail.com", role =
        c("aut", "cre"))
Description: Hi-C is a powerful technology for studying genome-wide
        chromatin interactions. However, current methods for assessing
        Hi-C data reproducibility can produce misleading results
        because they ignore spatial features in Hi-C data, such as
        domain structure and distance-dependence. We present a novel
        reproducibility measure that systematically takes these
        features into consideration. This measure can assess pairwise
        differences between Hi-C matrices under a wide range of
        settings, and can be used to determine optimal sequencing
        depth. Compared to existing approaches, it consistently shows
        higher accuracy in distinguishing subtle differences in
        reproducibility and depicting interrelationships of cell
        lineages than existing approaches. This R package `hicrep`
        implements our approach.
biocViews: Sequencing, HiC, QualityControl
Depends: R (>= 3.4)
Imports: stats
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/hicrep
git_branch: RELEASE_3_9
git_last_commit: f1dc914
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-02
NeedsCompilation: no
Packaged: 2019-05-03 04:38:45 UTC; biocbuild
Author: Tao Yang [aut, cre]
Maintainer: Tao Yang <xadmyangt@gmail.com>
Built: R 3.6.0; ; 2019-05-03 13:37:22 UTC; windows
