Package: MAVTgsa
Type: Package
Title: Three methods to identify differentially expressed gene sets,
ordinary least square test, Multivariate Analysis Of Variance
test with n contrasts and Random forest.
Version: 1.3
Date: 2014-05-27
Author: Chih-Yi Chien, Chen-An Tsai, Ching-Wei Chang, and James J. Chen
Maintainer: Chih-Yi Chien <92354503@nccu.edu.tw>
Depends: R (>= 2.13.2), corpcor, foreach, multcomp, randomForest, MASS
Description: This package is a gene set analysis function for one-sided test (OLS), two-sided test (multivariate analysis of variance).
If the experimental conditions are equal to 2, the p-value for Hotelling's t^2 test is calculated.
If the experimental conditions are great than 2, the p-value for Wilks' Lambda is determined and post-hoc test is reported too.
Three multiple comparison procedures, Dunnett, Tukey, and sequential pairwise comparison, are implemented.
The program computes the p-values and FDR (false discovery rate) q-values for all gene sets.
The p-values for individual genes in a significant gene set are also listed.
MAVTgsa generates two visualization output: a p-value plot of gene sets (GSA plot) and a GST-plot of the empirical distribution function of the ranked test statistics of a given gene set.
A Random Forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes.
License: GPL-2
LazyData: Yes
Repository: CRAN
Packaged: 2014-06-30 03:41:28 UTC; pelly
NeedsCompilation: no
Date/Publication: 2014-07-02 13:48:35

Author: AC Del Re & William T. Hoyt University of Wisconsin-Madison
Maintainer: AC Del Re <acdelre@gmail.com>
Description: This is an integrated meta-analysis package for conducting
a research synthesis with correlations. The unique feature of
this package is that there are user-friendly functions for
completing all statistical steps involved in a meta-analysis.
It uses recommended procedures as described in Cooper, Hedges,
& Valentine's Handbook of Research Synthesis and Meta-Analysis
Depends: R (>= 2.10.1), plyr, ggplot2, psych