Splice with Claude

I asked which RNA-splicing changes in liver cancer actually affect patient survival — and whether isoform switching correlated with survival rather than gene expression. Using only public data, I screened 23,909 splicing events in TCGA-LIHC against overall survival (382 significant, FDR<0.05), correlated splicing with matched protein abundance, and validated 18 survival-associated genes at the protein level in an independent cohort (CHCC-HBV deep proteome). I independently re-quantified tumor-vs-normal splicing with two orthogonal pipelines (SUPPA2 and LeafCutter), which agree on 90 genes (p=1.9×10⁻¹³). Running survival on the exact differentially-spliced events showed that 8 of 18 survival-defining genes, including the lead gene FN1, are prognostic through isoform switch alone, with no expression change: biology a conventional differential-expression analysis would miss. FN1's survival-linked exon is the IIICS/V oncofetal-fibronectin cassette, a splice-switching-ASO target hypothesis. Why it matters: I'm a wet-lab RNA-splicing PI. This is a multi-cohort, dual-pipeline proteogenomic + survival study that would normally need a bioinformatician, a splicing-methods specialist, and a biostatistician over months. With Claude Science I ran the whole thing myself, in days, including catching and correcting my own false leads and validating across two cohorts. The expertise was always mine; what changed is I no longer depend on a team to act on it and/ or move the field forward.