This package is for version 3.8 of Bioconductor; for the stable, up-to-date release version, see normr.
Bioconductor version: 3.8
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")
):
To install this package, start R (version "3.5") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("normr")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("normr")
HTML | R Script | Introduction to the normR package |
Reference Manual | ||
Text | NEWS |
biocViews | Alignment, Bayesian, ChIPSeq, Classification, DataImport, DifferentialPeakCalling, FunctionalGenomics, Genetics, MultipleComparison, Normalization, PeakDetection, Preprocessing, RIPSeq, Software |
Version | 1.8.0 |
In Bioconductor since | BioC 3.4 (R-3.3) (2.5 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 |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | normr_1.8.0.tar.gz |
Windows Binary | normr_1.8.0.zip |
Mac OS X 10.11 (El Capitan) | normr_1.8.0.tgz |
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 | http://bioconductor.org/packages/normr/ |
Package Downloads Report | Download Stats |
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