Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm

Hongxu Ding, Eugene F. Douglass, Adam M. Sonabend, Angeliki Mela, Sayantan Bose, Christian Gonzalez, Peter D. Canoll, Peter A. Sims, Mariano J. Alvarez () and Andrea Califano ()
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Hongxu Ding: Columbia University
Eugene F. Douglass: Columbia University
Adam M. Sonabend: Columbia University
Angeliki Mela: Columbia University
Sayantan Bose: Columbia University
Christian Gonzalez: Columbia University
Peter D. Canoll: Columbia University
Peter A. Sims: Columbia University
Mariano J. Alvarez: Columbia University
Andrea Califano: Columbia University

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack molecular profiles necessary for interactome inference (orphan tissues), or, as for single cells isolated from heterogeneous samples, their tissue context may be undetermined. To address this problem, we introduce metaVIPER, an algorithm designed to assess protein activity in tissue-independent fashion by integrative analysis of multiple, non-tissue-matched interactomes. This assumes that transcriptional targets of each protein will be recapitulated by one or more available interactomes. We confirm the algorithm’s value in assessing protein dysregulation induced by somatic mutations, as well as in assessing protein activity in orphan tissues and, most critically, in single cells, thus allowing transformation of noisy and potentially biased RNA-Seq signatures into reproducible protein-activity signatures.

Date: 2018
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DOI: 10.1038/s41467-018-03843-3

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