Classification of gene signatures for their information value and functional redundancy

Laura Cantini 1 Laurence Calzone Loredana Martignetti Mattias Rydenfelt Nils Blüthgen Emmanuel Barillot 2 Andrei Zinovyev 3
1 IBENS - Institut de biologie de l'ENS Paris (UMR 8197/1024)
2 CURIE-BIOINFO - Service de Bioinformatique
3 Cancer et génôme: Bioinformatique, biostatistiques et épidémiologie d'un système complexe
Abstract : Gene signatures are more and more used to interpret results of omics data analyses but suffer from compositional (large overlap) and functional (correlated read-outs) redundancy. Moreover, many gene signatures rarely come out as significant in statistical tests. Based on pan-cancer data analysis, we construct a restricted set of 962 signatures de fined as informative and demonstrate that they have a higher probability to appear enriched in comparative cancer studies. We show that the majority of informative signatures conserve their weights for the genes composing the signature (eigengenes) from one cancer type to another. We finally construct InfoSigMap, an interactive online map of these signatures and their cross correlations. This map highlights the structure of compositional and functional redundancies between informative signatures, and it charts the territories of biological functions. InfoSigMap can be used to visualize the results of omics data analyses and suggests a rearrangement of existing gene sets.
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https://hal-ens.archives-ouvertes.fr/hal-02129604
Contributeur : Laura Cantini <>
Soumis le : mercredi 15 mai 2019 - 09:30:07
Dernière modification le : mercredi 2 octobre 2019 - 11:51:05

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Laura Cantini, Laurence Calzone, Loredana Martignetti, Mattias Rydenfelt, Nils Blüthgen, et al.. Classification of gene signatures for their information value and functional redundancy. npj Systems Biology and Applications, Nature Research, 2018, 4 (1), ⟨10.1038/s41540-017-0038-8⟩. ⟨hal-02129604⟩

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