To install this package, start R and enter:

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

In most cases, you don't need to download the package archive at all.

normr

 

Normalization and difference calling in ChIP-seq data

Bioconductor version: Release (3.5)

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>

Citation (from within R, enter citation("normr")):

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 1.2.0
In Bioconductor since BioC 3.4 (R-3.3) (1 year)
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
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source normr_1.2.0.tar.gz
Windows Binary normr_1.2.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) normr_1.2.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/normr/tree/release-3.5
Package Short Url http://bioconductor.org/packages/normr/
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