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MMDiff (version 1.12.0)

Statistical Testing for ChIP-Seq data sets

Description

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). WARNING: This package is deprecated, please use MMDiff2 instead.

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Version

Version

1.12.0

License

Artistic-2.0

Maintainer

Gabriele Schweikert

Last Published

February 15th, 2017

Functions in MMDiff (1.12.0)

plotHistDists

plot MMD distances
findOutliers

Find peaks with extreme count values
Cfp1Dists

Example DBA object used to illustrate usage of the MMDiff package
MMD

DBAmmd Object for Cfp1 example
compHistDists

Compute distances between pairs of histograms
DBAmmd-Accessors

Extract data from DBAmmd objects
Cfp1-Peaks

Peaks for Cfp1-data set
Cfp1Profiles

Example DBA object used to illustrate usage of the MMDiff package
DBAmmd-class

Class DBAmmd
MMDiff-package

Statistical Testing for ChIP-Seq data sets
compHists

Compute Peak histograms
detPeakPvals

Compute p-values for each peak based on distances between histograms
getNormFactors

Determine Normalisation factors
getPeakProfiles

Add histograms (binned read enrichment profiles) to an existing DBA object
compPvals

compute p-values
compDists

Compute distances between Peaks
estimateFragmentCenters

estimate center of fragments
plotDISTS4Peak

plotDISTS4Peak
mm9-Genes

mm9-Genes
ui.MMDiff2

ui component for interactive visualization of MMD,GMD and Pearson Difference as well as plotting peaks
getPeakReads

Get reads from indexed bam files for defined regions
plotPeak

plot read enrichment profiles at a specific peak for all specified samples.
runShinyMMDiff2

Shiny Application for interactive visualization of MMD,GMD and Pearson Difference as well as plotting peaks
reportResults

report results
metaData

Generics for DBAmmd-Class
plotDists

plotDists
server.MMDiff2

Shiny server code for interactive visualization of MMD distances, peak plots, and MMD distances by sample.