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isma: an R package for the integrative analysis of mutations detected by multiple pipelines
BACKGROUND: Recent comparative studies have brought to our attention how somatic mutation detection from next-generation sequencing data is still an open issue in bioinformatics, because different pipelines result in a low consensus. In this context, it is suggested to integrate results from multipl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394085/ https://www.ncbi.nlm.nih.gov/pubmed/30819096 http://dx.doi.org/10.1186/s12859-019-2701-0 |
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author | Di Nanni, Noemi Moscatelli, Marco Gnocchi, Matteo Milanesi, Luciano Mosca, Ettore |
author_facet | Di Nanni, Noemi Moscatelli, Marco Gnocchi, Matteo Milanesi, Luciano Mosca, Ettore |
author_sort | Di Nanni, Noemi |
collection | PubMed |
description | BACKGROUND: Recent comparative studies have brought to our attention how somatic mutation detection from next-generation sequencing data is still an open issue in bioinformatics, because different pipelines result in a low consensus. In this context, it is suggested to integrate results from multiple calling tools, but this operation is not trivial and the burden of merging, comparing, filtering and explaining the results demands appropriate software. RESULTS: We developed isma (integrative somatic mutation analysis), an R package for the integrative analysis of somatic mutations detected by multiple pipelines for matched tumor-normal samples. The package provides a series of functions to quantify the consensus, estimate the variability, underline outliers, integrate evidences from publicly available mutation catalogues and filter sites. We illustrate the capabilities of isma analysing breast cancer somatic mutations generated by The Cancer Genome Atlas (TCGA) using four pipelines. CONCLUSIONS: Comparing different “points of view” on the same data, isma generates a unique mutation catalogue and a series of reports that underline common patterns, variability, as well as sites already catalogued by other studies (e.g. TCGA), so as to design and apply filtering strategies to screen more reliable sites. The package is available for non-commercial users at the URL https://www.itb.cnr.it/isma. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2701-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6394085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63940852019-03-11 isma: an R package for the integrative analysis of mutations detected by multiple pipelines Di Nanni, Noemi Moscatelli, Marco Gnocchi, Matteo Milanesi, Luciano Mosca, Ettore BMC Bioinformatics Software BACKGROUND: Recent comparative studies have brought to our attention how somatic mutation detection from next-generation sequencing data is still an open issue in bioinformatics, because different pipelines result in a low consensus. In this context, it is suggested to integrate results from multiple calling tools, but this operation is not trivial and the burden of merging, comparing, filtering and explaining the results demands appropriate software. RESULTS: We developed isma (integrative somatic mutation analysis), an R package for the integrative analysis of somatic mutations detected by multiple pipelines for matched tumor-normal samples. The package provides a series of functions to quantify the consensus, estimate the variability, underline outliers, integrate evidences from publicly available mutation catalogues and filter sites. We illustrate the capabilities of isma analysing breast cancer somatic mutations generated by The Cancer Genome Atlas (TCGA) using four pipelines. CONCLUSIONS: Comparing different “points of view” on the same data, isma generates a unique mutation catalogue and a series of reports that underline common patterns, variability, as well as sites already catalogued by other studies (e.g. TCGA), so as to design and apply filtering strategies to screen more reliable sites. The package is available for non-commercial users at the URL https://www.itb.cnr.it/isma. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2701-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-28 /pmc/articles/PMC6394085/ /pubmed/30819096 http://dx.doi.org/10.1186/s12859-019-2701-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Software Di Nanni, Noemi Moscatelli, Marco Gnocchi, Matteo Milanesi, Luciano Mosca, Ettore isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title | isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title_full | isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title_fullStr | isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title_full_unstemmed | isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title_short | isma: an R package for the integrative analysis of mutations detected by multiple pipelines |
title_sort | isma: an r package for the integrative analysis of mutations detected by multiple pipelines |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394085/ https://www.ncbi.nlm.nih.gov/pubmed/30819096 http://dx.doi.org/10.1186/s12859-019-2701-0 |
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