Package: LPE 1.87.0

Nitin Jain

LPE: Methods for analyzing microarray data using Local Pooled Error (LPE) method

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.

Authors:Nitin Jain <[email protected]>, Michael O'Connell <[email protected]>, Jae K. Lee <[email protected]>. Includes R source code contributed by HyungJun Cho <[email protected]>

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
LPE/json (API)

# Install 'LPE' in R:

install.packages('LPE', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Ley - Gene Expression Data from Mouse Immune response study,

On BioConductor:LPE-1.87.0(bioc 3.24)LPE-1.86.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarray differentialexpression

4.60 score 1 packages 22 scripts 3 mentions 16 exports 0 dependencies

Last updated from:6513337d22. Checks:1 ERROR, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	131
linux-devel-x86_64	OK	163
source / vignettes	OK	130
linux-release-x86_64	OK	125
macos-release-arm64	OK	75
macos-oldrel-arm64	OK	83
windows-devel	OK	67
windows-release	OK	59
windows-oldrel	OK	74
wasm-release	OK	96

Exports:am.trans baseOlig.error baseOlig.error.step1 baseOlig.error.step2 fdr.adjust fixbounds.predict.smooth.spline iqr lowess.normalize lpe mt.rawp2adjp.LPE n.genes.adaptive.int permute preprocess quan.norm quartile.normalize resamp.adj

Dependencies:

LPE test for microarray data with small number of replicates

Introduction | Analyzing data set using LPE library | Discussion

Rendered fromLPE.Rnwusingutils::Sweave

Last update: 2013-11-01
Started: 2013-11-01

Help page	Topics
Transform replicated arrays into (A,M) format	am.trans
Evaluates LPE variance function of M for quantiles of A within and experimental condition and then interpolates it for all genes.	baseOlig.error
Evaluates LPE variance function of M for quantiles of A within and experimental condition by divinding the A in 100 intervals.	baseOlig.error.step1
Evaluates LPE variance function of M for quantiles of A within and experimental condition. It is based on the adaptive number of intervals.	baseOlig.error.step2
FDR adjustment procedures	fdr.adjust
Makes the predicted variance non negative	fixbounds.predict.smooth.spline
Inter-quartile range	iqr
Gene Expression Data from Mouse Immune response study, (2002)	Ley
lowess normalization of the data (based on M vs A graph)	lowess.normalize
Evaluates local pooled error significance test	lpe
Adjusted p-values for simple multiple testing procedures	mt.rawp2adjp.LPE
Calcuates the number of genes in various intervals adaptively.	n.genes.adaptive.int
Calculating all possible permutations of a vector	permute
Preprocessing the data (IQR normalization, thresholding, log- transformation, and lowess normalization)	preprocess
Finding quartile range	quan.norm
Normalization based on quartile range	quartile.normalize
Resampling based fdr adjustment	resamp.adj

Package: LPE 1.87.0

LPE: Methods for analyzing microarray data using Local Pooled Error (LPE) method

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Usage by other packages (reverse dependencies)