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
| Maintainer | Johannes Helmuth <johannes.helmuth@laborberlin.com> |
| Author | Johannes Helmuth [aut, cre], Ho-Ryun Chung [aut] |
| License | GPL-2 |
| URL | https://github.com/your-highness/normR |
| Bug Reports | https://github.com/your-highness/normR/issues |
| System Requirements | C++11 |
| Downloads rank | 432 |
| Source branch | RELEASE_3_23 |
| biocViews | Alignment, Bayesian, ChIPSeq, Classification, DataImport, DifferentialPeakCalling, FunctionalGenomics, Genetics, MultipleComparison, Normalization, PeakDetection, Preprocessing, RIPSeq, Software |
Documentation
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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