pplr: R package for detecting differential gene expression
pplr is an R package that detects differential gene expression
by including probe-level measurement error and calculating the probability of positive log-ratio (PPLR).
It is a part of PUMA project.
There are two main reasons that make the detection of differential gene expression difficult. One is that the noisy nature of microarray data requires a reasonable probabilistic model to characterise the variability in probe data (within-chip variance). Another is that the small number of replicates makes it difficult to obtain an accurate variance estimate for each gene across replicates (between-replicate variance). Many approaches have been devised to address the second difficulty and obtain accurate between-replicate variance. Most of these methods are based on single point estimates of gene expression values. Few methods include within-chip variance in finding differential gene expression. pplr is used to include probe-level measurement error into the variance estimate of gene expression levels and makes use of this improved variance to detecting down and up-regulated genes by the calculation of the PPLR. The probe-level measurement error are calculated from the R package mmgmos.
||R version requirement
||Adding a seed to make sure the same results are obtained for each run.
Allow some conditions to have only one chip.
||Implementing MAP estimation 'map' for the Bayesian hierarchical model and replacing 'sha' with it.
Replacing the name of method 'shaconj' with 'em'.
||Fixing bugs for method 'sha'.
||Combining probe-level variance
with between-replicate variance and calculating PPLR to detect