preprocessData: Wrapper function to preprocess the data

In CSSQ: Chip-seq Signal Quantifier Pipeline

Description

This is a wrapper function that calls the functions to preprocess the data. It results in a RangedSummarizedExperiment-class object normalized counts and meta data that can be used by DBAnalyze.

Usage

preprocessData(
  inputRegions,
  sampleInfoFile,
  sampleDir = ".",
  inputCountData,
  numClusters = 4,
  noNeg = TRUE,
  plotDataToPDF = FALSE,
  ...
)

Arguments

inputRegions	A bed file the regions to analyze.
sampleInfoFile	A tab separated file all sample information. The following are the columns that are present in the file. * Sample Name : Names for the samples. * Group : The group the sample belongs. * IP : The name of the sample bam file. * IP_aligned_reads : The number of aligned reads in the sample. This is used in depth normalization process. * IN : The name of the sample's control bam file. * IN_aligned_reads : The number of aligned reads in the control file. This is used in depth normalization process.
sampleDir	Location of the input sample files in 'sampleInfoFile' file. (default: ".") Name,Group/Label,IP bam location,IP number of reads,IN bam location, IN number of reads).
inputCountData	The path to the file count data. This parameter is used when directly loading count data from a file. This should be a tab separated file sample names as header.
numClusters	A numerical parameter indicating the number of clusters to use in the normalization step. Passed on to normalizeData. (default: 4)
noNeg	A logical parameter indicating how to deal negative values. It is passed to ansTransform. (default: TRUE)
plotDataToPDF	A logical parameter indicating whether to make plots of the data distribution to a separate PDF file for each sample. It is passed on to passed to ansTransform. (default: FALSE)
...	Additional arguments passed on to getRegionCounts.

Value

RangedSummarizedExperiment-class containing the normalized counts, cluster information, the variance of the cluster in the sample and metadata.

See Also

getRegionCounts, ansTransform and normalizeData which this function calls

Examples

processedData <- preprocessData(system.file("extdata", "chr19_regions.bed",
package="CSSQ"),system.file("extdata", "sample_info.txt", package="CSSQ"),
sampleDir = system.file("extdata", package="CSSQ"),
numClusters=4,noNeg=TRUE,plotDataToPDF=FALSE)
processedData

CSSQ documentation built on Nov. 8, 2020, 6:47 p.m.