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normr

Normalization and difference calling in ChIP-seq data

Bioconductor version: 3.23 · Package version: 1.38.1

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.

Installation

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

BiocManager::install("normr")

Details

MaintainerJohannes Helmuth <johannes.helmuth@laborberlin.com>
AuthorJohannes Helmuth [aut, cre], Ho-Ryun Chung [aut]
LicenseGPL-2
URLhttps://github.com/your-highness/normR
Bug Reportshttps://github.com/your-highness/normR/issues
System RequirementsC++11
Downloads rank432
Source branchRELEASE_3_23
biocViewsAlignment, Bayesian, ChIPSeq, Classification, DataImport, DifferentialPeakCalling, FunctionalGenomics, Genetics, MultipleComparison, Normalization, PeakDetection, Preprocessing, RIPSeq, Software

Documentation

Download

Dependencies

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

Enhances: BiocParallel