This LPE library is used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional 'BH' or 'BY' procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions. To use it for paired data, see LPEP library. For using LPE in multiple conditions, use HEM library.
|Author||Nitin Jain <email@example.com>, Michael O'Connell <firstname.lastname@example.org>, Jae K. Lee <email@example.com>. Includes R source code contributed by HyungJun Cho <firstname.lastname@example.org>|
|Date of publication||None|
|Maintainer||Nitin Jain <email@example.com>|
|http://www.r-project.org, http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/, http://sourceforge.net/projects/r-lpe/|
am.trans: Transform replicated arrays into (A,M) format
baseOlig.error: Evaluates LPE variance function of M for quantiles of A...
baseOlig.error.step1: Evaluates LPE variance function of M for quantiles of A...
baseOlig.error.step2: Evaluates LPE variance function of M for quantiles of A...
fdr.adjust: FDR adjustment procedures
fixbounds.predict.smooth.spline: Makes the predicted variance non negative
iqr: Inter-quartile range
Ley: Gene Expression Data from Mouse Immune response study, (2002)
lowess.normalize: lowess normalization of the data (based on M vs A graph)
lpe: Evaluates local pooled error significance test
mt.rawp2adjp: Adjusted p-values for simple multiple testing procedures
n.genes.adaptive.int: Calcuates the number of genes in various intervals...
permute: Calculating all possible permutations of a vector
preprocess: Preprocessing the data (IQR normalization, thresholding, log-...
quan.norm: Finding quartile range
quartile.normalize: Normalization based on quartile range
resamp.adj: Resampling based fdr adjustment