RT Journal Article
SR Electronic
T1 Classification of gene signatures for their information value and functional redundancy
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 136499
DO 10.1101/136499
A1 Laura Cantini
A1 Laurence Calzone
A1 Loredana Martignetti
A1 Mattias Rydenfelt
A1 Nils Blüthgen
A1 Emmanuel Barillot
A1 Andrei Zinovyev
YR 2017
UL http://biorxiv.org/content/early/2017/05/10/136499.abstract
AB Large collections of gene signatures play a pivotal role in interpreting results of omics data analysis but suffer from compositional (large overlap) and functional (redundant read-outs) redundancy, and many gene signatures rarely pop-up in statistical tests. Based on pan-cancer data analysis, here we define a restricted set of 962 so called informative signatures and demonstrate that they have more chances to appear highly enriched in cancer biology studies. We show that the majority of informative signatures conserve their weights for the composing genes (eigengenes) from one cancer type to another. We construct InfoSigMap, an interactive online map showing the structure of compositional and functional redundancies between informative signatures and charting the territories of biological functions accessible through transcriptomic studies. InfoSigMap can be used to visualize in one insightful picture the results of comparative omics data analyses and suggests reconsidering existing annotations of certain reference gene set groups.