Titlebook: Variant Calling; Methods and Protocol Charlotte Ng,Salvatore Piscuoglio Book 2022 The Editor(s) (if applicable) and The Author(s), under ex

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Accurate Ensemble Prediction of Somatic Mutations with SMuRF2,ividual mutation callers using supervised machine learning. SMuRF2 provides an efficient workflow to predict both somatic point mutations (SNVs) and small insertions/deletions (indels) in cancer genomes and exomes. We describe the latest method and provide a detailed tutorial for running SMuRF2.

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Data Processing and Germline Variant Calling with the Sentieon Pipeline, data processing (Stephens et al.PLoS Biol 13:e1002195, 2015). The Sentieon. Genomics software enables rapid and accurate analysis of next-generation sequence data. In this work, we present a typical use of the Sentieon Genomics software for germline variant calling. The Sentieon germline variant ca

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MuSE: A Novel Approach to Mutation Calling with Sample-Specific Error Modeling,ave developed MuSE, . 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 p

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Detecting Medium and Large Insertions and Deletions with transIndel,due to challenges in distinguishing medium- and large-sized indels from RNA splicing events in RNA-seq data. We introduce transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on

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