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MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability

  • Xi'an Jiaotong University
  • Leiden University
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Jackson Laboratory

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)65-71
Number of pages7
JournalGenomics, proteomics & bioinformatics / Beijing Genomics Institute
Volume18
Issue number1
DOIs
StatePublished - Feb 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Microsatellite
  • Microsatellite instability
  • Multinomial distribution
  • Polymerase slippage
  • Tumor

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