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SomatoSim: precision simulation of somatic single nucleotide variants

BACKGROUND: Somatic single nucleotide variants have gained increased attention because of their role in cancer development and the widespread use of high-throughput sequencing techniques. The necessity to accurately identify these variants in sequencing data has led to a proliferation of somatic var...

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Autores principales: Hawari, Marwan A., Hong, Celine S., Biesecker, Leslie G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936459/
https://www.ncbi.nlm.nih.gov/pubmed/33676403
http://dx.doi.org/10.1186/s12859-021-04024-8
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author Hawari, Marwan A.
Hong, Celine S.
Biesecker, Leslie G.
author_facet Hawari, Marwan A.
Hong, Celine S.
Biesecker, Leslie G.
author_sort Hawari, Marwan A.
collection PubMed
description BACKGROUND: Somatic single nucleotide variants have gained increased attention because of their role in cancer development and the widespread use of high-throughput sequencing techniques. The necessity to accurately identify these variants in sequencing data has led to a proliferation of somatic variant calling tools. Additionally, the use of simulated data to assess the performance of these tools has become common practice, as there is no gold standard dataset for benchmarking performance. However, many existing somatic variant simulation tools are limited because they rely on generating entirely synthetic reads derived from a reference genome or because they do not allow for the precise customizability that would enable a more focused understanding of single nucleotide variant calling performance. RESULTS: SomatoSim is a tool that lets users simulate somatic single nucleotide variants in sequence alignment map (SAM/BAM) files with full control of the specific variant positions, number of variants, variant allele fractions, depth of coverage, read quality, and base quality, among other parameters. SomatoSim accomplishes this through a three-stage process: variant selection, where candidate positions are selected for simulation, variant simulation, where reads are selected and mutated, and variant evaluation, where SomatoSim summarizes the simulation results. CONCLUSIONS: SomatoSim is a user-friendly tool that offers a high level of customizability for simulating somatic single nucleotide variants. SomatoSim is available at https://github.com/BieseckerLab/SomatoSim.
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spelling pubmed-79364592021-03-08 SomatoSim: precision simulation of somatic single nucleotide variants Hawari, Marwan A. Hong, Celine S. Biesecker, Leslie G. BMC Bioinformatics Software BACKGROUND: Somatic single nucleotide variants have gained increased attention because of their role in cancer development and the widespread use of high-throughput sequencing techniques. The necessity to accurately identify these variants in sequencing data has led to a proliferation of somatic variant calling tools. Additionally, the use of simulated data to assess the performance of these tools has become common practice, as there is no gold standard dataset for benchmarking performance. However, many existing somatic variant simulation tools are limited because they rely on generating entirely synthetic reads derived from a reference genome or because they do not allow for the precise customizability that would enable a more focused understanding of single nucleotide variant calling performance. RESULTS: SomatoSim is a tool that lets users simulate somatic single nucleotide variants in sequence alignment map (SAM/BAM) files with full control of the specific variant positions, number of variants, variant allele fractions, depth of coverage, read quality, and base quality, among other parameters. SomatoSim accomplishes this through a three-stage process: variant selection, where candidate positions are selected for simulation, variant simulation, where reads are selected and mutated, and variant evaluation, where SomatoSim summarizes the simulation results. CONCLUSIONS: SomatoSim is a user-friendly tool that offers a high level of customizability for simulating somatic single nucleotide variants. SomatoSim is available at https://github.com/BieseckerLab/SomatoSim. BioMed Central 2021-03-06 /pmc/articles/PMC7936459/ /pubmed/33676403 http://dx.doi.org/10.1186/s12859-021-04024-8 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Hawari, Marwan A.
Hong, Celine S.
Biesecker, Leslie G.
SomatoSim: precision simulation of somatic single nucleotide variants
title SomatoSim: precision simulation of somatic single nucleotide variants
title_full SomatoSim: precision simulation of somatic single nucleotide variants
title_fullStr SomatoSim: precision simulation of somatic single nucleotide variants
title_full_unstemmed SomatoSim: precision simulation of somatic single nucleotide variants
title_short SomatoSim: precision simulation of somatic single nucleotide variants
title_sort somatosim: precision simulation of somatic single nucleotide variants
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936459/
https://www.ncbi.nlm.nih.gov/pubmed/33676403
http://dx.doi.org/10.1186/s12859-021-04024-8
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