normr

This is the development version of normr; for the stable release version, see normr.

Normalization and difference calling in ChIP-seq data

Bioconductor version: Development (3.22)

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 <johannes.helmuth at laborberlin.com>

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

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("normr")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Alignment, Bayesian, ChIPSeq, Classification, DataImport, DifferentialPeakCalling, FunctionalGenomics, Genetics, MultipleComparison, Normalization, PeakDetection, Preprocessing, RIPSeq, Software
Version	1.35.0
In Bioconductor since	BioC 3.4 (R-3.3) (8.5 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)
System Requirements	C++11
URL	https://github.com/your-highness/normR
Bug Reports	https://github.com/your-highness/normR/issues

Suggests	BiocStyle, testthat (>= 1.0), knitr, rmarkdown
Linking To	Rcpp
Enhances	BiocParallel
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/normr
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/normr
Package Short Url	https://bioconductor.org/packages/normr/
Package Downloads Report	Download Stats