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Introduction
Somatic mutations are present in all cells of the human body and occur throughout life. They are the consequence of multiple mutational processes, including the intrinsic slight infidelity of the DNA replication machinery, exogenous or endogenous mutagen exposures, enzymatic modification of DNA and defective DNA repair. Different mutational processes generate unique combinations of mutation types, termed “Mutational Signatures”.
In the past few years, large-scale analyses have revealed many mutational signatures across the spectrum of human cancer types, including the latest effort by the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Network (Alexandrov, L.B. et al., 2020) using data from more than 23,000 cancer patients.
Signature-based websites
Synapse audio dune 2 5 vst. As the number of mutational signatures and variant classes considered has increased, the need for a curated census of signatures has become apparent. Here, we deliver such a resource by providing a comprehensive overview of the key information known, suspected or widely discussed in the scientific literature for each of the identified mutational signatures on a dedicated website.
This summary includes the mutational profile, proposed aetiology and tissue distribution of each signature, as well as potential associations with other mutational signatures and how the signature has changed during iterations of analysis.
Nuke 12. Currently, three different variant classes are considered, resulting in the following sets of mutational signatures.
Versions
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Mutational signatures version 3 was released as part of COSMIC release v89 (May 2019) and updated to version 3.1 in COSMIC release v91 (June 2020). The version 3.1 update expands and improves upon the version 2 signatures (March 2015) that were part of earlier COSMIC releases and can still be consulted.
Bioinformatic tools
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The current set of mutational signatures has been extracted using SigProfiler, a compilation of publicly available bioinformatic tools addressing all the steps needed for signature identification. SigProfiler functionalities include mutation matrix generation from raw data and signature extraction, among others.