Splicing factors control exon inclusion in messenger RNAs, shaping transcriptome and proteome diversity. Their catalytic activity is regulated by multiple layers, making single-omic measurements on their own fall short in identifying which splicing factors underlie a phenotype. Here, we posit that splicing factor activity, defined as a splicing factor’s ability to modulate exon inclusion, can be estimated from changes in exon inclusion signatures. To test this hypothesis, we benchmark methods for constructing splicing factor→exon networks and estimating splicing factor activity. We find that combining RNA-seq perturbation-based networks with VIPER (Virtual Inference of Protein Activity by Enriched Regulon analysis) accurately captures splicing factor activity as modulated by multiple regulatory layers. This approach integrates splicing factor regulation into a single score derived solely from exon inclusion signatures, allowing functional interpretation of heterogeneous conditions. As a proof of concept, we identify recurrent cancer splicing programs, revealing associations with oncogenic- and tumor suppressor-like splicing factors missed by conventional methods. These programs correlate with patient survival and key cancer hallmarks: initiation, proliferation, and immune evasion. Altogether, we show splicing factor activity can be accurately estimated from exon inclusion changes, enabling comprehensive analyses of splicing regulation with minimal data requirements. Splicing factors shape how genes are stitched into RNA, but their activity is hard to measure. Here, the authors benchmark network methods and show exon-inclusion signatures infer splicing factor activity, uncovering cancer programs linked to survival and hallmarks.
Anglada-Girotto et al. (Thu,) studied this question.