A gene sets approach for identifying prognostic gene signatures for outcome prediction

doi:10.1186/1471-2164-9-177

BMC Genomics

Volume 9

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Methodology article

A gene sets approach for identifying prognostic gene signatures for outcome prediction

Seon-Young Kim and Yong Sung Kim

Human Genomics Laboratory, Functional Genomics Research Center, KRIBB, Daejeon 305-806, Korea

author email corresponding author email

BMC Genomics 2008, 9:177doi:10.1186/1471-2164-9-177


Published:	16 April 2008

Additional files

Additional file 1:

Additional data file 1 contains Supplementary tables (1–4) showing top 20 prognostic gene sets from three, four, five, and six means clustering of the 12 data sets.

Format: RTF Size: 415KB Download file

Additional file 2:

Additional data file 2 contains tables (5–7) showing adjusted hazard ratios of the gene set 11823860_ST2 for available clinical parameters in Sotiriou_2, van de Vijver, and Sorlie_1 datasets, respectively.

Format: RTF Size: 91KB Download file

Additional file 3:

Additional data file 3 is a Supplementary table (8) showing top 20 gene sets with high prediction accuracy in independent validation using nine datasets.

Format: RTF Size: 92KB Download file