Cancer Genomics Python Packages

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.

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.

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.

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.

mopepgen

Multi-Omics Peptide Generator

agfusion

Python package to annotate and visualize gene fusions.

lionheart

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

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.

cancer-data

Preprocessing for various cancer genomics datasets

somaticseq

An ensemble approach to accurately detect somatic mutations using SomaticSeq

pymaftools

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

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.

cbio-py

A Python client for the cbioPortal Cancer API.

maui-tools

Multi-omics Autoencoder Integration

str-mut-signatures

Extract STR signatures from annotated VCF

ngcgh

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

scatrex

Map single-cell transcriptomes to copy number evolutionary trees.

mimsi

Microsatellite Instability Classification using Multiple Instance Learning

fings

Filters for Next Generation Sequencing

sobolev-alignment

Sobolev alignment of deep probabilistic models for comparing single cell profiles

hrprofiler

HRD Prediction from WGS and WES samples

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.

psnv-hunter

Comprehensive visualization tool / dashboard to investigate and select Promoter SNVs (pSNVs) for downstream validation