calcSRmat

A matrix or a table containing two biological conditions
 dataset to process for detecting differentially expressed
 genes: <code>xdata</code>.

xdata

A vector containing the label names of the control samples:
 <code>cont</code> = c("cont01", "cont02", ...).

cont

A vector containing the label names of the test samples:
 <code>test</code> = c("test01", "test02", "test03", ...).

test

A scalar equals to 0 or 1. The value 0 (default) means that
 data in the matrix "xdata" are expressed in a log2 scale:
 <code>log2.opt</code> = 0

log2.opt

A scalar between 0 and 0.5. The value 0.25 (default) means
 that 25% of the lower and the upper rank values of each gene are not
 used for computing its statistics "ri", i.e. the interquartile range
 rank values are averaged: <code>trim.opt</code> = 0.25

trim.opt

This is an internal function used to calculate the sorted
rank matrix. It is used in the functions: fcros() and pfco().

A fold change rank based method is presented to search for genes with changing
expression and to detect recurrent chromosomal copy number aberrations. This
method may be useful for high-throughput biological data (micro-array, sequencing, ...).
Probabilities are associated with genes or probes in the data set and there is no
problem of multiple tests when using this method. For array-based comparative genomic
hybridization data, segmentation results are obtained by merging the significant
probes detected.

calcSRmat: Calculation of the sorted rank matrix from the dataset

Description

Usage

Arguments

References

Examples