SNPhood (version 1.2.3)

plotAndCalculateCorrelationDatasets: Calculate and plot correlation of region read counts among pairs of input files.

Description

plotAndCalculateCorrelationDatasets calculates and plots the pairwise correlation of all pairs of input files with among each other. The main purpose is to identify artefacts with particular files that should subsequently be excluded. The correlation is based on the raw region read counts(i.e., before binning). The results of the correlation analysis are stored in the SNPhood object. If the corrplot package is available, it will be used to produce a nice visualization of the correlation matrix.

Usage

plotAndCalculateCorrelationDatasets(SNPhood.o, fileToPlot = NULL, corMeasure = "pearson", verbose = FALSE, ...)

Arguments

SNPhood.o

Object of class SNPhood

fileToPlot

Character(1) or NULL. Default NULL. Filename of the PDF file for the output plots. If set to NULL, plots will be plotted to the currently active device.

corMeasure

Character(1). Default "pearson". The correlation measure that should be used to compare between pairs of samples. Either pearson, spearman, or kendall.

verbose

Logical(1). Default FALSE. Should the verbose mode (i.e., diagnostic messages during execution of the script) be enabled?

...

Additional arguments for the corrplot.mixed function from the corrplot package (if available).

Value

An object of type SNPhood, with the results of the correlation analysis stored in the slot "additionalResults". They can be retrieved via the helper function results for further investigation. The results consist of a named list with two elements: A correlation matrix of the region read counts across all input files and a translation table to correlate the input files with the abbreviations from the correlation plot.

Examples

data(SNPhood.o, package="SNPhood")
# Plot directly, using Pearson correlation
SNPhood.o = plotAndCalculateCorrelationDatasets(SNPhood.o)
# Plot to a PDF file
SNPhood.o = plotAndCalculateCorrelationDatasets(SNPhood.o, fileToPlot = "res.pdf")
# Using Spearman correlation instead of Pearson
SNPhood.o = plotAndCalculateCorrelationDatasets(SNPhood.o, corMeasure = "spearman")