Multiple sources of bias confound functional enrichment analysis of global -omics data.
Serious and underappreciated sources of bias mean that extreme caution should be applied when using or interpreting functional enrichment analysis to validate findings from global RNA- or protein-expression analyses.
Division of Genetics and Molecular Medicine, King's College London, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK. james.timmons@kcl.ac.uk.
James A
JA
Timmons
Division of Genetics and Molecular Medicine, King's College London, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK.
Krzysztof J
KJ
Szkop
School of Natural Sciences, University of Stirling, Stirling, FK9 4LA, UK.
Iain J
IJ
Gallagher
D020869:Gene Expression Profiling; D006801:Humans; D008099:Liver / Q000378:metabolism; D018482:Muscle, Skeletal / Q000378:metabolism; D009765:Obesity / Q000378:metabolism; D040901:Proteomics; D015983:Selection Bias; D017423:Sequence Analysis, RNA