# Significant Gene Expression Profile Differences in Time Course Microarray Data

## Documentation for package ‘maSigPro’ version 1.36.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

average.rows | Average rows by match and index
data.abiotic | Gene expression data potato abiotic stress
edesign.abiotic | Experimental design potato abiotic stress
edesign.OD | Experimental design with a measured independent variable
edesignCT | Experimental design with a shared time
edesignDR | Experimental design with different replicates
get.siggenes | Extract significant genes for sets of variables in time series gene expression experiments
i.rank | Ranks a vector to index
make.design.matrix | Make a design matrix for regression fit of time series gene expression experiments
maSigPro | Wrapping function for identifying significant differential gene expression profiles in micorarray time course experiments
maSigProUsersGuide | View maSigPro User's Guide
NBdata | RNA-Seq dataset example
NBdesign | Experimental design for RNA-Seq example
p.vector | Make regression fit for time series gene expression experiments
PlotGroups | Function for plotting gene expression profile at different experimental groups
PlotProfiles | Function for visualization of gene expression profiles
position | Column position of a variable in a data frame
reg.coeffs | Calculate true variables regression coefficients
see.genes | Wrapper function for visualization of gene expression values of time course experiments
stepback | Fitting a linear model by backward-stepwise regression
stepfor | Fitting a linear model by forward-stepwise regression
suma2Venn | Creates a Venn Diagram from a matrix of characters
T.fit | Makes a stepwise regression fit for time series gene expression experiments
two.ways.stepback | Fitting a linear model by backward-stepwise regression
two.ways.stepfor | Fitting a linear model by forward-stepwise regression