Version Compatibility

Reference examples tested with: ComplexHeatmap 2.18+, maftools 2.18+, comut 0.0.3+, MAFtools requires R 4.0+; comut.py requires pandas 2.0+, matplotlib 3.8+.

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

OncoPrint and Mutation Matrix Plots

"Plot mutations across a cohort" -> Render a gene-by-sample matrix where each cell stacks colored rectangles encoding alteration class (missense, truncating, splice, copy-gain, copy-loss, fusion). Sort samples by burden, optionally split by clinical group, and overlay co-mutation / mutual-exclusivity annotations. OncoPrint (Cerami 2012 Cancer Discov 2:401; canonical at cBioPortal) is the genre-defining visualization.

• R: ComplexHeatmap::oncoPrint, maftools::oncoplot
• Python: comut.CoMut, cbioportal-style implementations

The Single Most Important Modern Insight -- Cell Stacking Encodes Multiple Alterations Per Cell