Methodology article
Improving gene set analysis of microarray data by SAM-GS
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* Corresponding author: Yutaka Yasui yyasui@ualberta.ca
1 Department of Public Health Sciences, School of Public Health, University of Alberta, Edmonton, Alberta, T6G 2G3, Canada
2 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109-1024, USA
3 Division of Nephrology & Transplantation Immunology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, T6G 2S2, Canada
BMC Bioinformatics 2007, 8:242 doi:10.1186/1471-2105-8-242
Published: 5 July 2007Additional files
Additional file 1:
Gene-set simulation experiment results with the sex, p53, and leukemia datasets. The results of the gene-set simulation experiments using the three datasets are given.
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Additional file 2:
Histogram of Pearson correlation with the phenotype in the mouse-microarray kidney-transplant study. Histogram of Pearson correlation with the phenotype for 16,612 individual genes in the mouse-microarray kidney-transplant study.
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