MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data

@inproceedings{Fan2016MuSEAF,
  title={MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data},
  author={Yu Fan and Liu Xi and Daniel S. T. Hughes and Jianjun Zhang and Jianhua Zhang and P. Andrew Futreal and David A. Wheeler and Wenyi Wang},
  booktitle={Genome Biology},
  year={2016}
}
Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE… CONTINUE READING
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