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.

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.

agfusion

Python package to annotate and visualize gene fusions.

mopepgen

Multi-Omics Peptide Generator

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.

cancer-data

A unified downloader+preprocessor for cancer genomics datasets

lionheart

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

pymaftools

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

scope-bio

scOPE: single-cell Oncological Prediction Explorer — transfer-learning from bulk RNA-seq to predict per-cell mutation probabilities in scRNA-seq.

cbio-py

A Python client for the cbioPortal Cancer API.

maui-tools

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

sigpross

Decomposes mutational catalogues to mutational signatures

str-mut-signatures

Extract STR signatures from annotated VCF

somaticseq

An ensemble approach to accurately detect somatic mutations using SomaticSeq

scatrex

Map single-cell transcriptomes to copy number evolutionary trees.

ngcgh

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

fings

Filters for Next Generation Sequencing

mimsi

A deep, multiple instance learning based classifier for identifying Microsatellite Instability from NGS

hrprofiler

HRD Prediction from WGS and WES samples

sobolev-alignment

Sobolev alignment of deep probabilistic models for comparing single cell profiles

new-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.