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DChIPRep (version 1.2.3)

DChIPRep - Analysis of chromatin modification ChIP-Seq data with replication

Description

The DChIPRep package implements a methodology to assess differences between chromatin modification profiles in replicated ChIP-Seq studies as described in Chabbert et. al - http://www.dx.doi.org/10.15252/msb.20145776. A detailed description of the method is given in the software paper at https://doi.org/10.7717/peerj.1981

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Version

Version

1.2.3

License

MIT + file LICENCE

Maintainer

Bernd Klaus

Last Published

February 15th, 2017

Functions in DChIPRep (1.2.3)

getMATfromDataFrame

Helper function to turn a data.frame into a matrix and remove the ID column.

importData_soGGi

Import the data from bam files directly

exampleChipData

An example ChIP data.

exampleSampleTable

An example sample table data.frame

DChIPRepResults-class

DChIPRepResults object and constructor

Accessor and setter for the 'FDRresults' slot of a DChIPRepResults object.

A test DESeqDataSet

prints the DESeq2Data slot of the DChIPRepResults object

Run the tests on a DChIPRepResults object.

resultsDChIPRep

Accessors and setter for the 'results' slot of a DChIPRepResults object.

summarizeCountsPerPosition

Helper function to summarize the counts per position

Accessors for the 'DESeq2Data' slot of a DChIPRepResults object.

Import the data after running the Python script

plotSignificance

Produce a plot that colors the positions identified as significant

DChIPRep: A package for differential analysis of histone modification ChIP-Seq profiles

Another example Input data set that can be used with importDataFromMatrices from rom Galonska et. al., 2015.

Produce a TSS plot of the two conditions in the data

exampleInputData

An example input data.

sample_table_galonska

Another example sample table based on data from rom Galonska et. al., 2015.

Another example ChIP data set that can be used with importDataFromMatrices from rom Galonska et. al., 2015.

importDataFromMatrices

Import the data from ChiP and input matrices

TSS around called peak regions from Galonska et. al.