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.
Package details |
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Author | Johannes Helmuth [aut, cre], Ho-Ryun Chung [aut] |
Bioconductor views | Alignment Bayesian ChIPSeq Classification DataImport DifferentialPeakCalling FunctionalGenomics Genetics MultipleComparison Normalization PeakDetection Preprocessing RIPSeq |
Maintainer | Johannes Helmuth <johannes.helmuth@laborberlin.com> |
License | GPL-2 |
Version | 1.19.3 |
URL | https://github.com/your-highness/normR |
Package repository | View on GitHub |
Installation |
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