DCE500: Gene expression dataset containing top 500 differentially...

In uc-bd2k/gimmR: This package was built to cluster gene expression data using the Gaussian Infinite Mixture Model.

Description

This dataset was derived from the Schmidt et al. (2008) primary breast tumor data set by identifying the top 500 differentially co-expressed genes using the DCIM algorithm.

Usage

data(DCE500)

Format

A data frame with 500 observations on the following 202 variables.

Details

see our support page http://eh3.uc.edu/gimm/dcim/

Source

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11121

References

Schmidt M, Böhm D, von Törne C, Steiner E et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res 2008 Jul 1;68(13):5405-13. http://www.ncbi.nlm.nih.gov/sites/entrez?Db=Pubmed&term=18593943[UID]

Examples

data(DCE500)
gimmOut <- runGimmNPosthoc(DCE500, dataFile="DCE500", M=200, T=500, estimate_contexts="y", intFiles=FALSE, verbose=TRUE, nIter=500, burnIn=250)
drawHeatmap(gimmOut, scale="none")

uc-bd2k/gimmR documentation built on May 3, 2019, 2:15 p.m.