Somatic Variants 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.

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.

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.

somaticseq

An ensemble approach to accurately detect somatic mutations using SomaticSeq

probabilistic2020

Simulates somatic mutations, and calls statistically significant oncogenes and tumor suppressor genes based on a randomization-based test

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.