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MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability
Microsatellite instability (MSI) is a key biomarker for cancer therapy and prognosis. Traditional experimental assays are laborious and time-consuming, and next-generation sequencing-based computational methods do not work on leukemia samples, paraffin-embedded samples, or patient-derived xenografts...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393535/ https://www.ncbi.nlm.nih.gov/pubmed/32171661 http://dx.doi.org/10.1016/j.gpb.2020.02.001 |
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author | Jia, Peng Yang, Xiaofei Guo, Li Liu, Bowen Lin, Jiadong Liang, Hao Sun, Jianyong Zhang, Chengsheng Ye, Kai |
author_facet | Jia, Peng Yang, Xiaofei Guo, Li Liu, Bowen Lin, Jiadong Liang, Hao Sun, Jianyong Zhang, Chengsheng Ye, Kai |
author_sort | Jia, Peng |
collection | PubMed |
description | Microsatellite instability (MSI) is a key biomarker for cancer therapy and prognosis. Traditional experimental assays are laborious and time-consuming, and next-generation sequencing-based computational methods do not work on leukemia samples, paraffin-embedded samples, or patient-derived xenografts/organoids, due to the requirement of matched normal samples. Herein, we developed MSIsensor-pro, an open-source single sample MSI scoring method for research and clinical applications. MSIsensor-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative site selection method to enable MSI detection without matched normal samples. We demonstrate that MSIsensor-pro is an ultrafast, accurate, and robust MSI calling method. Using samples with various sequencing depths and tumor purities, MSIsensor-pro significantly outperformed the current leading methods in both accuracy and computational cost. MSIsensor-pro is available at https://github.com/xjtu-omics/msisensor-pro and free for non-commercial use, while a commercial license is provided upon request. |
format | Online Article Text |
id | pubmed-7393535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73935352020-08-04 MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability Jia, Peng Yang, Xiaofei Guo, Li Liu, Bowen Lin, Jiadong Liang, Hao Sun, Jianyong Zhang, Chengsheng Ye, Kai Genomics Proteomics Bioinformatics Method Microsatellite instability (MSI) is a key biomarker for cancer therapy and prognosis. Traditional experimental assays are laborious and time-consuming, and next-generation sequencing-based computational methods do not work on leukemia samples, paraffin-embedded samples, or patient-derived xenografts/organoids, due to the requirement of matched normal samples. Herein, we developed MSIsensor-pro, an open-source single sample MSI scoring method for research and clinical applications. MSIsensor-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative site selection method to enable MSI detection without matched normal samples. We demonstrate that MSIsensor-pro is an ultrafast, accurate, and robust MSI calling method. Using samples with various sequencing depths and tumor purities, MSIsensor-pro significantly outperformed the current leading methods in both accuracy and computational cost. MSIsensor-pro is available at https://github.com/xjtu-omics/msisensor-pro and free for non-commercial use, while a commercial license is provided upon request. Elsevier 2020-02 2020-03-12 /pmc/articles/PMC7393535/ /pubmed/32171661 http://dx.doi.org/10.1016/j.gpb.2020.02.001 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Method Jia, Peng Yang, Xiaofei Guo, Li Liu, Bowen Lin, Jiadong Liang, Hao Sun, Jianyong Zhang, Chengsheng Ye, Kai MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title | MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title_full | MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title_fullStr | MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title_full_unstemmed | MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title_short | MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability |
title_sort | msisensor-pro: fast, accurate, and matched-normal-sample-free detection of microsatellite instability |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393535/ https://www.ncbi.nlm.nih.gov/pubmed/32171661 http://dx.doi.org/10.1016/j.gpb.2020.02.001 |
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