MuSE: A Novel Approach to Mutation Calling with Sample-Specific Error Modeling.

Methods Mol Biol

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Published: June 2022

Accurate detection of somatic mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We have developed MuSE, Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of tumor and normal tissue at each reference base. It adopts a sample-specific error model to depict inter-tumor heterogeneity, which greatly improves the overall accuracy. Here, we describe the method and provide a tutorial on the installation and application of MuSE.

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Source
http://dx.doi.org/10.1007/978-1-0716-2293-3_2DOI Listing

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