MethodThe LeFE algorithm: embracing the complexity of gene expression in the interpretation of microarray data1 Genomics and Bioinformatics Groups, Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA 2 Bioinformatics Program, Boston University, Cummington St, Boston, Massachusetts 02215, USA 3 Virginia Commonwealth University, Biostatistics Department, E Marshall St, Richmond, Virginia 23284, USA 4 SRA International, Fair Lakes Court, Fairfax, Virginia 22033, USA
Genome Biology 2007, 8:R187doi:10.1186/gb-2007-8-9-r187
Subject areas: Bioinformatics, Genome studies Additional filesAdditional 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 |


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