Package: maSigPro 1.85.0

Maria Jose Nueda

maSigPro: Significant Gene Expression Profile Differences in Time Course Gene Expression Data

maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray and RNA-Seq experiments.

Authors:Ana Conesa and Maria Jose Nueda

maSigPro_1.85.0.tar.gz
maSigPro_1.85.0.zip(r-4.7)maSigPro_1.85.0.zip(r-4.6)maSigPro_1.85.0.zip(r-4.5)
maSigPro_1.85.0.tgz(r-4.6-any)maSigPro_1.85.0.tgz(r-4.5-any)
maSigPro_1.85.0.tar.gz(r-4.7-any)maSigPro_1.85.0.tar.gz(r-4.6-any)
maSigPro_1.85.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
maSigPro/json (API)

# Install 'maSigPro' in R:

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

Datasets:

data.abiotic - Gene expression data potato abiotic stress
edesign.abiotic - Experimental design potato abiotic stress
edesignCT - Experimental design with a shared time
edesignDR - Experimental design with different replicates
ISOdata - RNA-Seq dataset example for isoforms
ISOdesign - Experimental design for ISOdata dataset example
NBdata - RNA-Seq dataset example
NBdesign - Experimental design for RNA-Seq example

On BioConductor:maSigPro-1.85.0(bioc 3.24)maSigPro-1.84.0(bioc 3.23)

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

microarray rna-seq differential expression timecourse

5.58 score 189 scripts 119 mentions 24 exports 7 dependencies

Last updated from:2feb456308. Checks:1 ERROR, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	130
linux-devel-x86_64	OK	254
source / vignettes	OK	159
linux-release-x86_64	OK	219
macos-release-arm64	OK	117
macos-oldrel-arm64	OK	118
windows-devel	OK	156
windows-release	OK	158
windows-oldrel	OK	181
wasm-release	OK	78

Exports:average.rows get.siggenes getDS getDSPatterns i.rank IsoModel IsoPlot make.design.matrix maSigProUsersGuide p.vector PlotGroups PlotProfiles PodiumChange position reg.coeffs see.genes seeDS stepback stepfor suma2Venn T.fit tableDS two.ways.stepback two.ways.stepfor

Dependencies:admisc Biobase BiocGenerics generics MASS mclust venn

maSigPro Vignette

Rendered frommaSigPro.Rnwusingutils::Sweave

Last update: 2020-04-09
Started: 2013-10-21

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Average rows by match and index	average.rows
Gene expression data potato abiotic stress	data.abiotic
Experimental design potato abiotic stress	edesign.abiotic
Experimental design with a shared time	edesignCT
Experimental design with different replicates	edesignDR
Extract significant genes for sets of variables in time series gene expression experiments	get.siggenes
Extract lists of significant isoforms from Differentially Spliced Genes (DSG)	getDS
Lists of genes with Isoforms in different clusters	getDSPatterns
Ranks a vector to index	i.rank
RNA-Seq dataset example for isoforms	ISOdata
Experimental design for ISOdata dataset example	ISOdesign
Detection of genes with Isoforms with different gene expression in time course experiments	IsoModel
Plotting the isoform profiles of a specific gene by groups	IsoPlot
Make a design matrix for regression fit of time series gene expression experiments	make.design.matrix
View maSigPro User's Guide	maSigProUsersGuide
RNA-Seq dataset example	NBdata
Experimental design for RNA-Seq example	NBdesign
Make regression fit for time series gene expression experiments	p.vector
Function for plotting gene expression profile at different experimental groups	PlotGroups
Function for visualization of gene expression profiles	PlotProfiles
Detection of Genes with switchs of their major isoforms	PodiumChange
Column position of a variable in a data frame	position
Calculate true variables regression coefficients	reg.coeffs
Wrapper function for visualization of gene expression values of time course experiments	see.genes
Wrapper function for visualization of significant isoforms from Differentially Spliced Genes	seeDS
Fitting a linear model by backward-stepwise regression	stepback
Fitting a linear model by forward-stepwise regression	stepfor
Creates a Venn Diagram from a matrix of characters	suma2Venn
Makes a stepwise regression fit for time series gene expression experiments	T.fit
Identification of Mayor and minor Isoforms in the clusters	tableDS
Fitting a linear model by backward-stepwise regression	two.ways.stepback
Fitting a linear model by forward-stepwise regression	two.ways.stepfor