Methodology article
RCMAT: a regularized covariance matrix approach to testing gene sets
-
* Corresponding author: Mark A Reimers mreimers@vcu.edu
Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia 23298, USA
BMC Bioinformatics 2009, 10:300 doi:10.1186/1471-2105-10-300
Published: 21 September 2009Additional files
Additional file 1:
Summary statistics of the RCMAT nominal p-values under the simulated non-null conditions. Under each of 36 select conditions (the number of variables/genes defined in the gene set, the sample size of each phenotype, the amount of nonzero separation as a multiple of an eigenvector representing the variance/correlation structure within the gene set, the separation occurs on either the major or a minor axis of variation) 100 simulation experiments were performed and permutation p-values obtained. For each condition various percentiles for the p-values obtained are listed.
Format: DOC Size: 81KB Download file
This file can be viewed with: Microsoft Word Viewer
Additional file 2:
Comparison of RCMAT with the procedure of Kong et al. For each of the gene sets from Mootha et al. [3] both the RCMAT and the method of Kong et al. were applied. Nominal (unadjusted) permutation p-values for each of the two procedures are given. The number of genes in the pathway is also provided.
Format: DOC Size: 217KB Download file
This file can be viewed with: Microsoft Word Viewer