Exon inclusion signatures enable accurate estimation of splicing factor activity.

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Splicing factors control exon inclusion in messenger RNA, 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 propose splicing factor activity can be estimated by interpreting changes in exon inclusion. We benchmark methods to construct splicing factor→exon networks and calculate activity. Combining RNA-seq perturbation-based networks with VIPER (virtual inference of protein activity by enriched regulon analysis) accurately captures splicing factor activation modulated by different regulatory layers. This approach consolidates 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 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.