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MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations

Microsatellite instability (MSI) is a form of hypermutation that occurs in some tumors due to defects in cellular DNA mismatch repair. MSI is characterized by frequent somatic mutations (i.e., cancer-specific mutations) that change the length of simple repeats (e.g., AAAAA…., GATAGATAGATA...). Clini...

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Autores principales: Ni Huang, Mi, McPherson, John R., Cutcutache, Ioana, Teh, Bin Tean, Tan, Patrick, Rozen, Steven G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549793/
https://www.ncbi.nlm.nih.gov/pubmed/26306458
http://dx.doi.org/10.1038/srep13321
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author Ni Huang, Mi
McPherson, John R.
Cutcutache, Ioana
Teh, Bin Tean
Tan, Patrick
Rozen, Steven G.
author_facet Ni Huang, Mi
McPherson, John R.
Cutcutache, Ioana
Teh, Bin Tean
Tan, Patrick
Rozen, Steven G.
author_sort Ni Huang, Mi
collection PubMed
description Microsatellite instability (MSI) is a form of hypermutation that occurs in some tumors due to defects in cellular DNA mismatch repair. MSI is characterized by frequent somatic mutations (i.e., cancer-specific mutations) that change the length of simple repeats (e.g., AAAAA…., GATAGATAGATA...). Clinical MSI tests evaluate the lengths of a handful of simple repeat sites, while next-generation sequencing can assay many more sites and offers a much more complete view of their somatic mutation frequencies. Using somatic mutation data from the exomes of a 361-tumor training set, we developed classifiers to determine MSI status based on four machine-learning frameworks. All frameworks had high accuracy, and after choosing one we determined that it had >98% concordance with clinical tests in a separate 163-tumor test set. Furthermore, this classifier retained high concordance even when classifying tumors based on subsets of whole-exome data. We have released a CRAN R package, MSIseq, based on this classifier. MSIseq is faster and simpler to use than software that requires large files of aligned sequenced reads. MSIseq will be useful for genomic studies in which clinical MSI test results are unavailable and for detecting possible misclassifications by clinical tests.
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spelling pubmed-45497932015-09-04 MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations Ni Huang, Mi McPherson, John R. Cutcutache, Ioana Teh, Bin Tean Tan, Patrick Rozen, Steven G. Sci Rep Article Microsatellite instability (MSI) is a form of hypermutation that occurs in some tumors due to defects in cellular DNA mismatch repair. MSI is characterized by frequent somatic mutations (i.e., cancer-specific mutations) that change the length of simple repeats (e.g., AAAAA…., GATAGATAGATA...). Clinical MSI tests evaluate the lengths of a handful of simple repeat sites, while next-generation sequencing can assay many more sites and offers a much more complete view of their somatic mutation frequencies. Using somatic mutation data from the exomes of a 361-tumor training set, we developed classifiers to determine MSI status based on four machine-learning frameworks. All frameworks had high accuracy, and after choosing one we determined that it had >98% concordance with clinical tests in a separate 163-tumor test set. Furthermore, this classifier retained high concordance even when classifying tumors based on subsets of whole-exome data. We have released a CRAN R package, MSIseq, based on this classifier. MSIseq is faster and simpler to use than software that requires large files of aligned sequenced reads. MSIseq will be useful for genomic studies in which clinical MSI test results are unavailable and for detecting possible misclassifications by clinical tests. Nature Publishing Group 2015-08-26 /pmc/articles/PMC4549793/ /pubmed/26306458 http://dx.doi.org/10.1038/srep13321 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Ni Huang, Mi
McPherson, John R.
Cutcutache, Ioana
Teh, Bin Tean
Tan, Patrick
Rozen, Steven G.
MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title_full MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title_fullStr MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title_full_unstemmed MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title_short MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations
title_sort msiseq: software for assessing microsatellite instability from catalogs of somatic mutations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549793/
https://www.ncbi.nlm.nih.gov/pubmed/26306458
http://dx.doi.org/10.1038/srep13321
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