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Treffer: SomaticSiMu: a mutational signature simulator.

Title:
SomaticSiMu: a mutational signature simulator.
Authors:
Chen D; Department of Biology, Western University, London, ON N6A 5B7, Canada., Randhawa GS; School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada., Soltysiak MPM; Department of Biology, Western University, London, ON N6A 5B7, Canada., de Souza CPE; Department of Statistical and Actuarial Sciences, Western University, London, ON N6A 5B7, Canada., Kari L; School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada., Singh SM; Department of Biology, Western University, London, ON N6A 5B7, Canada., Hill KA; Department of Biology, Western University, London, ON N6A 5B7, Canada.
Source:
Bioinformatics (Oxford, England) [Bioinformatics] 2022 Apr 28; Vol. 38 (9), pp. 2619-2620.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: Oxford : Oxford University Press, c1998-
MeSH Terms:
Software* , Genomics*, Reproducibility of Results ; Mutation ; Genome
Entry Date(s):
Date Created: 20220308 Date Completed: 20221114 Latest Revision: 20221201
Update Code:
20250114
DOI:
10.1093/bioinformatics/btac128
PMID:
35258549
Database:
MEDLINE

Weitere Informationen

Summary: SomaticSiMu is an in silico simulator of single and double base substitutions, and single base insertions and deletions in an input genomic sequence to mimic mutational signatures. SomaticSiMu outputs simulated DNA sequences and mutational catalogues with imposed mutational signatures. The tool is the first mutational signature simulator featuring a graphical user interface, control of mutation rates and built-in visualization tools of the simulated mutations. Simulated datasets are useful as a ground truth to test the accuracy and sensitivity of DNA sequence classification tools and mutational signature extraction tools under different experimental scenarios. The reliability of SomaticSiMu was affirmed by (i) supervised machine learning classification of simulated sequences with different mutation types and burdens, and (ii) mutational signature extraction from simulated mutational catalogues.
Availability and Implementation: SomaticSiMu is written in Python 3.8.3. The open-source code, documentation and tutorials are available at https://github.com/HillLab/SomaticSiMu under the terms of the CreativeCommonsAttribution4.0InternationalLicense.
Supplementary Information: Supplementary data are available at Bioinformatics online.
(© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)