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maSigPro (version 1.44.0)

Significant Gene Expression Profile Differences in Time Course Microarray Data

Description

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 experiments.

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Version

Version

1.44.0

License

GPL (>= 2)

Maintainer

Maria Jose Nueda

Last Published

February 15th, 2017

Functions in maSigPro (1.44.0)

Experimental design with a shared time

make.design.matrix

Make a design matrix for regression fit of time series gene expression experiments

Experimental design with different replicates

Experimental design with a measured independent variable

Column position of a variable in a data frame

Fitting a linear model by forward-stepwise regression

two.ways.stepfor

Fitting a linear model by forward-stepwise regression

Experimental design for RNA-Seq example

RNA-Seq dataset example

Creates a Venn Diagram from a matrix of characters

Calculate true variables regression coefficients

Gene expression data potato abiotic stress

Function for visualization of gene expression profiles

Ranks a vector to index

Function for plotting gene expression profile at different experimental groups

Extract significant genes for sets of variables in time series gene expression experiments

edesign.abiotic

Experimental design potato abiotic stress

Fitting a linear model by backward-stepwise regression

Wrapping function for identifying significant differential gene expression profiles in micorarray time course experiments

Average rows by match and index

Make regression fit for time series gene expression experiments

Wrapper function for visualization of gene expression values of time course experiments

Makes a stepwise regression fit for time series gene expression experiments

two.ways.stepback

Fitting a linear model by backward-stepwise regression

maSigProUsersGuide

View maSigPro User's Guide