make.design.matrix: Make a design matrix for regression fit of time series gene...

In mjnueda/maSigPro: Significant Gene Expression Profile Differences in Time Course Gene Expression Data

Description

make.design.matrix creates the design matrix of dummies for fitting time series micorarray gene expression experiments.

Usage

make.design.matrix(edesign, degree = 2, time.col = 1,
                   repl.col = 2, group.cols = c(3:ncol(edesign)))

Arguments

edesign	matrix describing experimental design. Rows must be arrays and columns experiment descriptors
degree	the degree of the regression fit polynome. degree = 1 returns linear regression, degree = 2 returns quadratic regression, etc
time.col	column number in edesign containing time values. Default is first column
repl.col	column number in edesign containing coding for replicate arrays. Default is second column
group.cols	column numbers in edesign indicating the coding for each experimental group (treatment, tissue, ...). See details

Details

rownames of edesign object should contain the arrays naming (i.e. array1, array2, ...). colnames of edesign must contain the names of experiment descriptors(i.e. "Time", "Replicates", "Treatment A", "Treatment B", etc.). for each experimental group a different column must be present in edesign, coding with 1 and 0 whether each array belongs to that group or not.

make.design.matrix returns a design matrix where rows represent arrays and column variables of time, dummies and their interactions for up to the degree given. Dummies show the relative effect of each experimental group related to the first one. Single dummies indicate the abcissa component of each group. $Time*dummy$ variables indicate slope changes, $Time^2*dummy$ indicates curvature changes. Higher grade values could model complex responses. In case experimental groups share a initial state (i.e. common time 0), no single dummies are modeled.

Value

dis	design matrix of dummies for fitting time series
groups.vector	vector coding the experimental group to which each variable belongs to
edesign	edesign value passed as argument

Author(s)

Ana Conesa and Maria Jose Nueda, [e-mail]

References

Conesa, A., Nueda M.J., Alberto Ferrer, A., Talon, T. 2006. maSigPro: a Method to Identify Significant Differential Expression Profiles in Time-Course Microarray Experiments. Bioinformatics 22, 1096-1102

Examples

data(edesign.abiotic, edesignCT)
make.design.matrix(edesign.abiotic)  # quadratic model
make.design.matrix(edesignCT, degree = 3)  # cubic model with common starting time point

mjnueda/maSigPro documentation built on Dec. 11, 2020, 12:21 a.m.