Somatic Variants Collection

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🔥Fire

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“Bayesian haplotype-based mutation calling”

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📦Normal

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

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🔮Psychic

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“An ensemble approach to accurately detect somatic mutations using SomaticSeq”

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🔮Psychic

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“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. ”

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🔮Psychic

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“NeuSomatic: Deep convolutional neural networks for accurate somatic mutation detection”

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📦Normal

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“🌲 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”

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🔮Psychic

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“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. ”

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🔥Flame

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“SNV calling from single cell sequencing”

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🔮Psychic

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

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📦Normal

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

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🔮Psychic

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

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🔮Psychic

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“Snakemake-based workflow for detecting structural variants in genomic data”

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🔮Psychic

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“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.”