normr

DOI: 10.18129/B9.bioc.normr    

Normalization and difference calling in ChIP-seq data

Bioconductor version: Release (3.6)

Robust normalization and difference calling procedures for ChIP-seq and alike data. Read counts are modeled jointly as a binomial mixture model with a user-specified number of components. A fitted background estimate accounts for the effect of enrichment in certain regions and, therefore, represents an appropriate null hypothesis. This robust background is used to identify significantly enriched or depleted regions.

Author: Johannes Helmuth [aut, cre], Ho-Ryun Chung [aut]

Maintainer: Johannes Helmuth <helmuth at molgen.mpg.de>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("normr")

Documentation

HTML	R Script	Introduction to the normR package
PDF		Reference Manual
Text		NEWS

Details

biocViews	Alignment, Bayesian, ChIPSeq, Classification, DataImport, DifferentialPeakCalling, FunctionalGenomics, Genetics, MultipleComparison, Normalization, PeakDetection, Preprocessing, RIPSeq, Software
Version	1.4.0
In Bioconductor since	BioC 3.4 (R-3.3) (1.5 years)
License	GPL-2
Depends	R (>= 3.3.0)
Imports	methods, stats, utils, grDevices, parallel, GenomeInfoDb, GenomicRanges, IRanges, Rcpp (>= 0.11), qvalue(>= 2.2), bamsignals(>= 1.4), rtracklayer(>= 1.32)
LinkingTo	Rcpp
Suggests	BiocStyle, testthat (>= 1.0), knitr, rmarkdown
SystemRequirements	C++11
Enhances	BiocParallel
URL	https://github.com/your-highness/normR
BugReports	https://github.com/your-highness/normR/issues
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	normr_1.4.0.tar.gz
Windows Binary	normr_1.4.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan)	normr_1.4.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/normr
Package Short Url	http://bioconductor.org/packages/normr/
Package Downloads Report	Download Stats