To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MMDiff")
In most cases, you don't need to download the package archive at all.
MMDiff
Statistical Testing for ChIP-Seq data sets
Bioconductor version: 3.0
This package detects statistically significant difference between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD).
Author: Gabriele Schweikert
Maintainer: Gabriele Schweikert <G.Schweikert at ed.ac.uk>
Citation (from within R,
enter citation("MMDiff")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MMDiff")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MMDiff")
| R Script | Analysing ChIP-Seq data with the "MMDiff" package | |
| Reference Manual |
Details
| biocViews | ChIPSeq, MultipleComparison, Software |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | Artistic-2.0 |
| Depends | R (>= 2.14.0), GenomicRanges, parallel, DiffBind, GMD, Rsamtools |
| Imports | GenomicRanges, IRanges, Biobase |
| LinkingTo | |
| Suggests | MMDiffBamSubset |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | MMDiffBamSubset |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | MMDiff_1.6.0.tar.gz |
| Windows Binary | MMDiff_1.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | MMDiff_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | MMDiff_1.6.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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