MAVTn: OLS, Hottelling's T2 and MANOVA with n contrasts

In MAVTgsa: Three methods to identify differentially expressed gene sets, ordinary least square test, Multivariate Analysis Of Variance test with n contrasts and Random forest.

Description

A gene set analysis functions for computiong the p-values for one-sided test (OLS) and two-sided test (multivariate analysis of variance). If the experimental conditions are equal to 2, the p-value for Hotelling's t square test is calculated. If the experimental conditions are great than 2, the p-value for Wilks' Lambda is deterimined and post-hoc test is reported too. The p-value for individual gene test of significant gene sets are also listed.

Usage

MAVTn(DATA, GS, MCP = 1, alpha = 0.01, nbPerm = 5000)

Arguments

DATA	an (m+1) x n gene expression data matrix with n samples in columns. The first row contains the information of experimental condition of each sample. The genes are expressed in the rest m rows.
GS	an m x k binary matrix with code (0, 1), where k is the number of gene sets. Each column represents a pre-defined gene set.
MCP	the choice for one of three multiple comparison methods, Dunnett = 1, Tuckey = 2, Sequential pairwise = 3.
alpha	the significant level
nbPerm	the number of permutation specified

Value

The p-values of OLS and MANOVA test are returned. If there is any significant gene set, the p values for individual genes in the gene set will be reported.

Note

R > 2.13.2

Author(s)

Chih-Yi Chien, Chen-An Tsai, Ching-Wei Chang, and James J. Chen

References

Chen,J.J. et al. (2007) Significance analysis of group of genes in expression profiling studies, Bioinformatics, 23, 2104.

Tsai,C.A. et al. (2009) Multivariate analysis of variance test for gene set analysis. Bioinformatics, 25, 897.

Examples

#------------simulate data matrix---------------#

data(data)
data(GS)

MAVTn(data,GS,MCP=1, nbPerm = 100)

MAVTgsa documentation built on May 2, 2019, 6:37 a.m.