DChIPRep
(Package: DChIPRep) :
DChIPRep: A package for differential analysis of histone modification ChIP-Seq profiles
The DChIPRep package provides functions to perform a differential analysis of histone modification profiles at base-pair resolution
● Data Source:
BioConductor
● Keywords:
● Alias: DChIPRep, DChIPRep-package
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The DChIPRepResults contains a DESeqDataSet as obtained after the initial import.
● Data Source:
BioConductor
● Keywords:
● Alias: DChIPRepResults, DChIPRepResults-class
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DESeq2Data
(Package: DChIPRep) :
Accessors for the 'DESeq2Data' slot of a code{DChIPRepResults
The slot contains the DESeqDataSet as it is obtained after the initial data import. The DESeqDataSet contains the counts per position and the normalization factors as computed using the input counts.
● Data Source:
BioConductor
● Keywords:
● Alias: DESeq2Data, DESeq2Data,DChIPRepResults-method, DESeq2Data<-, DESeq2Data<-,DChIPRepResults,DESeqDataSet-method
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FDRresults
(Package: DChIPRep) :
Accessor and setter for the 'FDRresults' slot of a code{DChIPRepResults
The slot contains the results of the FDR estimation as performed within the function runTesting. It is the complete output of the fdrtool function.
● Data Source:
BioConductor
● Keywords:
● Alias: FDRresults, FDRresults,DChIPRepResults-method, FDRresults<-, FDRresults<-,DChIPRepResults,list-method
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getMATfromDataFrame
(Package: DChIPRep) :
Helper function to turn a data.frame into a matrix
This function takes a data.frame, with the genomic features (e.g. transcripts or genes) in the rows and the positions upstream and downstream of the TSS in the columns as well as a column ID containing a genomic feature ID and returns the data.frame with the ID column removed. The input for this function are tables obtained after running the Python import script.
● Data Source:
BioConductor
● Keywords:
● Alias: getMATfromDataFrame
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importData
(Package: DChIPRep) :
Import the data after running the Python script
This function imports the data from the count table files as returned by the accompanying Python script.
● Data Source:
BioConductor
● Keywords:
● Alias: importData
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This function imports the data from two matrices that contain counts summarized per position. It computes the normalization factors from the input (one per position) and creates a DChIPRepResults object.
● Data Source:
BioConductor
● Keywords:
● Alias: importDataFromMatrices
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importData_soGGi
(Package: DChIPRep) :
Import the data from bam files directly
This function imports the data from .bam files directly. It will return a matrix with one column per .bam file and the respective counts per postion in the rows. It uses the function regionPlot from the package soGGi.
● Data Source:
BioConductor
● Keywords:
● Alias: importData_soGGi
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plotProfiles
(Package: DChIPRep) :
Produce a TSS plot of the two conditions in the data
This function plots the positionwise mean of the log2 of the normalized counts of the two conditions after runTesting has been run on a DChIPRepResults object.
● Data Source:
BioConductor
● Keywords:
● Alias: plotProfiles, plotProfiles,DChIPRepResults-method
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plotSignificance
(Package: DChIPRep) :
Produce a plot that colors the positions identified as significant
This function plots the positionwise mean of the two conditions after runTesting has been run on a DChIPRepResults object. The points corresponding to significant positions are colored black in both of the conditions. The function returns the plot as a ggplot2 object that can be modified afterwards.
● Data Source:
BioConductor
● Keywords:
● Alias: plotSignificance, plotSignificance,DChIPRepResults-method
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