Bayesian haplotype-based mutation calling

DeepSomatic is an analysis pipeline that uses a deep neural network to call somatic variants from tumor-normal and tumor-only sequencing data.

An ensemble approach to accurately detect somatic mutations using SomaticSeq

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.

NeuSomatic: Deep convolutional neural networks for accurate somatic mutation detection

🌲 An easy-to-use and scalable toolkit for genomic alteration signature (a.k.a. mutational signature) analysis and visualization in R https://shixiangwang.github.io/sigminer/reference/index.html

SNV calling from single cell sequencing

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.

ClairS - a deep-learning method for long-read somatic small variant calling

R data package for pre-compiled somatic mutations from TCGA cohorts and CCLE

Snakemake-based workflow for detecting structural variants in genomic data

ClairS-TO - a deep-learning method for tumor-only somatic variant calling

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.

Classifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests

Clinical Whole Genome and Exome Sequencing Pipeline

Dockstore implementation of CGP core WGS analysis

A BioWDL variantcalling pipeline for germline DNA data. Starting with FASTQ files to produce VCF files. Category:Multi-Sample

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.

Pipeline for Somatic Variant Calling with WES and WGS data

SigProfilerSimulator allows realistic simulations of mutational patterns and mutational signatures in cancer genomes. The tool can be used to simulate signatures of single point mutations, double point mutations, and insertion/deletions. Further, the tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

Transposon Insertion Finder - Detection of new TE insertions in NGS data

R wrapper for utilizing the SigProfilerMatrixGenerator framework

A suite of bioinformatics data processing and analysis pipelines, software, and training resources for common methods.

highly-efficient & lightweight mutation signature matrix aggregation

Accucopy is a computational method that infers Allele-Specific Copy Number alterations from low-coverage low-purity tumor sequencing data.

An R wrapper for SigProfilerExtractor that 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.

A long-read somatic phasing software for tumor-only sequencing

nRex: Germline and somatic single-nucleotide, short indel and structural variant calling

A long-read somatic phasing software for tumor-normal paired sequencing

An R wrapper for running the SigProfilerPlotting framework