betr {betr}R Documentation

Bayesian Estimation of Temporal Regulation (BETR): Calculate the probability of differential expression in time-course data

Description

Calculate the probability of differential expression of each feature in a microarray gene expression time-course data set.

Usage

betr(eset, cond=NULL, timepoint, replicate, twoColor = FALSE, twoCondition = NULL, alpha = 0.05, verbose=FALSE)

Arguments

eset object of class matrix, ExpressionSet or exprSet containing log-ratios or log-values of expression for a series of microarrays
cond character or factor vector giving the experimental group for each sample of eset. Not required for a single-condition time-course.
timepoint numeric vector giving the time point for each sample of eset
replicate character or factor vector giving the replicate ID of each sample of eset
twoColor boolean indicating whether the data is from a two-color microarray platform
twoCondition boolean indicating whether the data is from a two condition experiment (as opposed to a single condition experiment where the comparison is between baseline and subsequent time points)
alpha the desired False Discovery Rate
verbose whether to output more detailed information about the model fitting

Details

This function fits a model to estimate the probability of differential for each feature of time-course data set.

Value

a numeric vector of the probability of differential expression for each feature in the data set.

Author(s)

Martin Aryee

References

The algorithm is described in detail in: (..undergoing review..)

Examples

library(Biobase)    
data(timeEset)
prob <- betr(timeEset, cond=pData(timeEset)$strain, 
    timepoint=pData(timeEset)$time, replicate=pData(timeEset)$rep, alpha=0.05)
head(prob)

[Package betr version 1.0.0 Index]