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.

微卫星不稳定性（MSI）是癌症治疗和预后的关键生物标志物。传统的实验分析费力且费时，并且由于需要匹配的正常样本，因此基于下一代测序的计算方法不适用于白血病样本，石蜡包埋的样本或患者来源的异种移植物/有机体。在此，我们开发了MSIsensor-pro，这是一种开源的单样本MSI评分方法，用于研究和临床应用。MSIsensor-pro引入了多项分布模型来量化每种肿瘤的聚合酶滑移样品和区分性位点选择方法，可在没有匹配的正常样品的情况下进行MSI检测。我们证明了MSIsensor-pro是一种超快速，准确和强大的MSI调用方法。使用具有各种测序深度和肿瘤纯度的样品，MSIsensor-pro在准确性和计算成本上均明显优于当前的领先方法。MSIsensor-pro可在https://github.com/xjtu-omics/msisensor-pro上获得，对于非商业用途是免费的，而可根据要求提供商业许可。