Pan-cancer analysis for a gene across all 33 TCGA cancer types plus DepMap and CPTAC. Use this skill when the user asks for pan-cancer analysis, cross-cancer comparison, multi-cancer gene report, or wants to analyze a gene across ALL cancer types at once. Generates a comprehensive PDF report with expression, survival (KM curves + log-rank), mutation, copy-number, DepMap cell-line data, and CPTAC protein data. Covers TCGA expression + survival, TCGA mutation/CNA survival, DepMap 26Q1 expression/copy-number/mutations, and CPTAC proteomics.
DepMap analysis for a gene across CANCER CELL LINES (NOT patient samples). Modules: expression, mutation, copy number, essentiality. Data is streamed directly from the DepMap API — no full dataset download needed. Also includes standalone co-expression (depmap_coexpression.py) and co-essentiality (depmap_coessentiality.py) scripts for cell-line correlations. For patient/tumor co-expression use coexpression-for-gene (TCGA/GTEx) instead.
Co-expression in PATIENT SAMPLES (TCGA tumors / GTEx normal tissues). NOT for cell lines — use depmap_coexpression.py for DepMap cell-line co-expression. Fetches real TCGA expression from cBioPortal API (PanCancer Atlas). GTEx requires user-provided expression file.
Run Cox proportional hazards regression on clinical and molecular data. Fits univariate and multivariate Cox models, computes hazard ratios with confidence intervals, tests the proportional hazards assumption, and generates forest plots and Schoenfeld residual plots.
Correlate gene expression or dependency scores with drug sensitivity data from PRISM (DepMap). Identifies drugs whose sensitivity correlates with the gene's expression or essentiality, and generates correlation plots.
Analyze TCGA somatic mutations in a gene via cBioPortal API (PanCancer Atlas). Supports local TCGA MAF file as fallback. Computes mutation frequencies, identifies hotspot residues, classifies mutation types, and generates lollipop plots and summaries.
Retrieve and summarize normal tissue expression for a single human gene using GTEx, including full tissue-level expression, publication-quality barplot output, and a simple expression-pattern classification such as universally expressed, tissue-specific, mixed, or non-expressed.
Query and visualise TCGA expression data for a single gene across cancer cohorts. Supports pan-cancer bar plots, single-cohort boxplots, and tumor-vs-normal comparisons. All data is fetched live from the GDC API — no local files required.