tprobaCalc

This is an internal function for using a C code to
perform a Student one sample test for each row of the full or
reduced matrix with sorted rank values.

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.

Doulaye Dembele

fcros

A Method to Search for Differentially Expressed Genes and to
Detect Recurrent Chromosomal Copy Number Aberrations

tprobaCalc function

<dl> <dt>moy</dt>
<dd>Vector containing average of rank values for rows</dd> <dt>std</dt>
<dd>Vector containing standard deviation of rank values for rows</dd> <dt>n</dt>
<dd>Number of genes or probes in the dataset</dd> <dt>dl</dt>
<dd>Degree of freedom in the test. This is equal to the number of 
 the columns in the full or reduced matrix of sorted rank values 
 minus one</dd> <dt>em</dt>
<dd>Expected average rank values for each row</dd></dl>

Arguments

Author

Calculation of the Student one sample test probabilities — tprobaCalc

<dl>

 <dt>moy</dt>
<dd>Vector containing average of rank values for rows</dd>

 <dt>std</dt>
<dd>Vector containing standard deviation of rank values for rows</dd>

 <dt>n</dt>
<dd>Number of genes or probes in the dataset</dd>

 <dt>dl</dt>
<dd>Degree of freedom in the test. This is equal to the number of 
 the columns in the full or reduced matrix of sorted rank values 
 minus one</dd>

 <dt>em</dt>
<dd>Expected average rank values for each row</dd>

</dl>

tprobaCalc: Calculation of the Student one sample test probabilities

Description

Usage

Arguments

Author

References

Examples