VIPER (Virtual Inference of Protein-activity by Enriched Regulon analysis)

Overview

VIPER infers the activity of transcription factors and other signaling proteins (“master regulators”) from bulk or single-cell gene expression data, using pre-built transcriptional regulatory networks (regulons) from tools such as ARACNe. For each candidate regulator, VIPER computes a normalized enrichment score over the expression signatures of its transcriptional targets, analogous to GSEA. Because mRNA levels of signaling proteins often do not reflect protein activity, VIPER provides a protein-activity estimate from RNA data without direct proteomics measurements.

Used by

• Applied to RNA-seq profiles of 28 metastatic neuroendocrine neoplasms (pog570_bcgsc_2020) to perform master-regulator inference; Cluster B NENs showed MYC family activation, and Cluster A showed relative inhibition of MEN1 and DAXX compared with other clusters PMID:24326773.
• VIPER-style regulon analysis applied to 23 candidate transcription factor regulators in 408 BLCA RNA-seq samples; identified GATA3, FOXA1, PPARG as luminal drivers and TP63, EGFR as basal-squamous discriminators; validated in independent Sjödahl 308-sample cohort PMID:28988769

Notes

• Requires a tissue-matched regulon; pan-cancer regulons (e.g., from TCGA ARACNe networks) may not be optimal for rare tumor types.
• VIPER and metaVIPER (multi-network) are available as the R/Bioconductor package viper.
• Commonly combined with clustering or enrichment analyses to identify co-activated transcriptional programs.

Sources

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