The LeFE algorithm: embracing the complexity of gene expression in the interpretation of microarray data

Gabriel S Eichler¹^,2 , Mark Reimers¹^,3 , David Kane¹^,4 and John N Weinstein¹

¹Genomics and Bioinformatics Groups, Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA

²Bioinformatics Program, Boston University, Cummington St, Boston, Massachusetts 02215, USA

³Virginia Commonwealth University, Biostatistics Department, E Marshall St, Richmond, Virginia 23284, USA

⁴SRA International, Fair Lakes Court, Fairfax, Virginia 22033, USA

author email corresponding author email

Genome Biology 2007, 8:R187doi:10.1186/gb-2007-8-9-r187


Published:	10 September 2007

Subject areas: Bioinformatics, Genome studies

Additional files

Additional data file 1:

Complete results from the smoker/never-smoker demonstration, including gene categories ranked by LeFE computed median permutation t-test P value and individual gene importance scores.

Format: XLS Size: 777KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional data file 2:

Complete results from the breast cancer demonstration, including gene categories ranked by LeFE computed median permutation t-test P value and individual gene importance scores.

Format: XLS Size: 746KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional data file 3:

Complete results from the gefitinib demonstration, including gene categories ranked by LeFE computed median permutation t-test P value and individual gene importance scores.

Format: XLS Size: 665KB Download file

This file can be viewed with: Microsoft Excel Viewer