SomaticSignatures: inferring mutational signatures from single-nucleotide variants

By Julian S. Gehring, Bernd Fischer, Michael F. Lawrence, Wolfgang Huber. bioRxiv, 2014

304 citations recorded by the source corpus.

Mutational signatures are patterns in the occurrence of somatic single nucleotide variants (SNVs) that can reflect underlying mutational processes. The SomaticSignatures package provides flexible, interoperable, and easy-to-use tools that identify such signatures in cancer sequencing data. It facilitates large-scale, cross-dataset estimation of mutational signatures, implements existing methods for pattern decomposition, supports extension through user-defined methods and integrates with Bioconductor workflows. The R package SomaticSignatures is available as part of the Bioconductor project (R Core Team, 2014; Gentleman et al., 2004). Its documentation provides additional details on the methodology and demonstrates applications to biological datasets.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f21f25c4ff0fd96eacae71961bacaedfd6f12acb

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Citations in the corpus

• Integrative molecular and clinical modeling of clinical outcomes to PD-1 blockade in metastatic melanoma patients (2019, unknown): “Mutational Signatures— De novo mutational signatures were generated in this cohort using an adaptation of NMF 70 using the Brunet update method 71 as previously described in detail 51 , using the R-packages SomaticSignatures 72 and NMF 73 .”
• Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer. (2018, unknown): “De novomutation signatures were derived using non-negative matrix factorization implemented in the SomaticSignatures R package (Gehring et al., 2015).”
• MutationalPatterns: comprehensive genome-wide analysis of mutational processes (2016, background): “MutSpec [43] Somatic Signatures [44] deconstruc tSigs [45] EMu [46] Language/ is an important feature.”