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metagene: A package to produce Metafeature plots

This repository contains R functions used to do multiple ChIP-Seq experiments comparisons.

This package produces Metagene-like plots to compare the behavior of DNA-interacting proteins at selected groups of features. A typical analysis can be done in viscinity of transcription start sites (TSS) of genes or at any regions of interest (such as enhancers). Multiple combinations of group of features and/or group of bam files can be compared in a single analysis. Bootstraping analysis is used to compare the groups and locate regions with statistically different enrichment profiles. In order to increase the sensitivity of the analysis, alignment data is used instead of peaks produced with peak callers (i.e.: MACS2 or PICS). The metagene package uses bootstrap to obtain a better estimation of the mean enrichment and the confidence interval for every group of samples.

Currently supported species are human and mouse.

Authors

Charles Joly Beauparlant, Fabien Claude Lamaze, Rawane Samb, Astrid Louise Deschenes and Arnaud Droit.

See Arnaud Droit Lab website.

License

This package and the underlying metagene code are distributed under the Artistic license 2.0. You are free to use and redistribute this software.

For more information on Artistic 2.0 License see http://opensource.org/licenses/Artistic-2.0

Bugs/Feature requests

If you have any bugs or feature requests, let us know. Thanks!

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Version

Version

1.0.0

License

Artistic-2.0

Maintainer

Charles Joly Beauparlant

Last Published

February 15th, 2017

Functions in metagene (1.0.0)

prepareBamFiles

Prepare bam files before parsing.
binMatrix

Bin matrix columns
scaleVector

Scale the values of a vector to fit with predetermined size
prepareFeatures

Convert a list of IDs into a GRangesList
scaleVectors

Resize the vectors of every group so they have the same length.
bootstrapAnalysis

Perform the bootstrap analysis
getGenes

Fetch the annotation of all genes.
getDataFrame

Convert the bootstrapped data into a data.frame
plotGraphic

Produce a plot with based on a data.frame
plotMatrices

Create a graph
applyOnGroups

Apply a function on every groups of the main data structure
parseFeatures

Parse an experiment using a list of features
binBootstrap

Estimate mean and confidence interval of a column using bootstrap.
parseRegions

Parse an experiment using regions that can be of different length.
getGenesBiomart

Fetch the annotation of all genes from biomart.
mergeMatrix

Convert list of vectors in matrix for a single group
rawCountsToRPM

Convert the raw counts into reads per million aligned (rpm)
removeControls

Substract controls from a single group
parseBamFile

Parse a single bam file
parseBamFiles

Parse multiple bamFiles
prepareGroups

Distribute the bam filenames in their respective groups.
prepareRegions

Parse bed files and convert them in a list of GRangesList.