Cancer Genomics Python Packages

sigprofilermatrixgenerator

SigProfilerMatrixGenerator creates mutational matrices for all types of somatic mutations. It allows downsizing the generated mutations only to parts for the genome (e.g., exome or a custom BED file). The tool seamlessly integrates with other SigProfiler tools.

sigprofilertopography

SigProfilerTopography allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures.

sigprofilerplotting

SigProfilerPlotting provides a standard tool for displaying all types of mutational signatures as well as all types of mutational patterns in cancer genomes. The tool seamlessly integrates with other SigProfiler tools.

sigprofilerextractor

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

biomedical-ai-skills

AI agent skills for cancer biology and multi-omics research

octopusv

Merge and compare structural variants across callers, samples, and platforms. Standardizes BND-heavy output from GRIDSS, SvABA, Sniffles, and more.

sigproextractor

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

trialmatchai

TrialMatchAI leverages large language models to streamline clinical trial matching by evaluating patient-specific clinical characteristics against trial eligibility criteria and generating relevant, ranked trial recommendations.

bindsight

Expression to Binder: joins cohort RNA-seq target discovery to de novo protein binder design in one reproducible workflow, with PROV-O/RO-Crate provenance from every ranked binder back to the patient samples.

agfusion

Python package to annotate and visualize gene fusions.

sigpross

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

mopepgen

Multi-Omics Peptide Generator

cancer-data

A unified downloader+preprocessor for cancer genomics datasets

pymaftools

A Python toolkit for MAF files and multi-omics cancer genomics — parsing, analysis, ML, and publication-ready visualization.

lionheart

LIONHEART detects cancer from whole genome sequenced plasma cell-free DNA.

cbio-py

A Python client for the cbioPortal Cancer API.

scope-bio

scOPE learns mutation-linked expression programs from bulk RNA-seq and projects them into single-cell RNA-seq to infer per-cell mutation probabilities, revealing subclonal evolutionary structure that complements CNV analyses.

maui-tools

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

somaticseq

An ensemble approach to accurately detect somatic mutations using SomaticSeq

str-mut-signatures

Extract STR signatures from annotated VCF

scatrex

Map single-cell transcriptomes to copy number evolutionary trees.

fings

Filters for Next Generation Sequencing

ngcgh

Tools for producing pseudo-cgh of next-generation sequencing data

hrprofiler

Homologous Recombination Profiler (HRProfiler) is a classification tool that predicts the HRD probability for both whole-genome and exome-sequenced samples using HRD-specific mutation and copy number features.