| Literature DB >> 32171661 |
Peng Jia1, Xiaofei Yang2, Li Guo3, Bowen Liu1, Jiadong Lin4, Hao Liang1, Jianyong Sun5, Chengsheng Zhang6, Kai Ye7.
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.Entities:
Keywords: Microsatellite; Microsatellite instability; Multinomial distribution; Polymerase slippage; Tumor
Year: 2020 PMID: 32171661 DOI: 10.1016/j.gpb.2020.02.001
Source DB: PubMed Journal: Genomics Proteomics Bioinformatics ISSN: 1672-0229 Impact factor: 7.691