Fig. 6: C-G2P decodes relationships between complex genotypes and tumour-intrinsic and microenvironmental phenotypes.

a, Identification of genotype–phenotype relationships. Comparison of the prevalence of perturbations between phenotypic groups and the remainder of the nodules (total n = 324) for tumour-intrinsic phenotypes (top) and TME (bottom) using ORs. OR > 1 indicates enrichment of perturbations within the phenotypic group; OR < 1 indicates depletion (Methods). The number of nodules with a given phenotype (n) is indicated. Note that groups are not mutually exclusive. The median and 90% CI are reported. Significant relationships are indicated (exact P values are provided); two-tailed deviations from one, computed with 20,000 samples from the posterior (Methods); ***P < 0.001, **P < 0.01, *P < 0.05. b, Identification of genotype–phenotype relationships for genes associated with cholangiocytes. A GLM model predicts gene expression signals at each 10X Visium spot using estimated probabilities of perturbation presence (Methods). Feature coefficients, shown as the mean and 3σ CIs, indicate associations between gene expression and perturbations for representative transcripts. Bayesian modelling of perturbation probabilities was used to infer the occurrence of individual perturbations per nodule (Methods). Data are derived from 324 nodules across six topographically separated regions used for 10X Visium from a single RUBIX experiment with two animals.