Fig. 4: Functional architecture of antimicrobial-resistance and virulence signatures in CRC.
From: Cross-cohort resistome and virulome gradients structure the colorectal cancer microbiome
a, b Total antimicrobial-resistance gene (ARG) and virulence-factor (VF) loads across Healthy, Adenoma and Cancer groups show no global differences in abundance. c Bootstrapped PLS-Double-Machine-Learning (PLS-DML) effects showing component-level average treatment effects (ATEs). d Sensitivity of estimated effects to unmeasured confounding quantified by E-values; PLS₃ shows greatest robustness. e Directed acyclic graph (DAG) illustrating assumptions linking ARG/VF abundance (indicated in the figure as Microbial_abundance) to CRC stage while adjusting for age, BMI and sex. f Gene co-occurrence network highlighting interactions between dominant ARG and VF modules along the CRC continuum. Red node = PLS₁ and green node = PLS₃. g External-validation ROC curve showing moderate discrimination of the derived functional signatures (AUC = 0.603). h Directional concordance of PLS₁/PLS₃ genes between internal and external datasets indicating consistent trends. i Power analysis for PLS₁ and PLS₃ components demonstrating statistical power > 80% at current sample size. j Gene-level ANOVA-based power estimates confirming adequate detectability for the most robust genes under about 100 samples per group.
