MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine

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the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine</title> <meta name="description" content="MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine"> <meta name="keywords" content="microsatellite instability, pan-cancer classification, somatic mutation, support vector machine"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div 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class="card"> <div class="card-body"><strong>Paper Count:</strong> 87408</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen%20Wang">Chen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun%20Liang"> Chun Liang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite (MS) length due to a deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important indicator for tumor prognostic. Conventional clinical diagnosis of MSI examines PCR products of a panel of MS markers using electrophoresis (MSI-PCR) which is laborious, time consuming, and less reliable. MSIpred, a python 2 package for automatic classification of MSI was released by this study. It computes important somatic mutation features from files in mutation annotation format (MAF) generated from paired tumor-normal exome sequencing data, subsequently using these to predict tumor MSI status with a support vector machine (SVM) classifier trained by MAF files of 1074 tumors belonging to four types. Evaluation of MSIpred on an independent 358-tumor test set achieved overall accuracy of over 98% and area under receiver operating characteristic (ROC) curve of 0.967. These results indicated that MSIpred is a robust pan-cancer MSI classification tool and can serve as a complementary diagnostic to MSI-PCR in MSI diagnosis. <iframe src="https://publications.waset.org/abstracts/93236.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microsatellite%20instability" title="microsatellite instability">microsatellite instability</a>, <a href="https://publications.waset.org/abstracts/search?q=pan-cancer%20classification" title=" pan-cancer classification"> pan-cancer classification</a>, <a href="https://publications.waset.org/abstracts/search?q=somatic%20mutation" title=" somatic mutation"> somatic mutation</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/93236/msipred-a-python-2-package-for-the-classification-of-tumor-microsatellite-instability-from-tumor-mutation-annotation-data-using-a-support-vector-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93236.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET 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MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine