%0 Journal Article %1 Fan:2016:Genome-Biol:27557938 %A Fan, Y %A Xi, L %A Hughes, D S %A Zhang, J %A Zhang, J %A Futreal, P A %A Wheeler, D A %A Wang, W %D 2016 %J Genome Biol %K cancer-research exome fulltext gdc pipeline shouldread software variant-calling wxs %N 1 %P 178-178 %R 10.1186/s13059-016-1029-6 %T MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data %U https://pubmed.ncbi.nlm.nih.gov/27557938/ %V 17 %X 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 adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.

@article{Fan:2016:Genome-Biol:27557938, abstract = {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 adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.}, added-at = {2020-08-02T20:43:41.000+0200}, author = {Fan, Y and Xi, L and Hughes, D S and Zhang, J and Zhang, J and Futreal, P A and Wheeler, D A and Wang, W}, biburl = {https://www.bibsonomy.org/bibtex/26f006628d206d1b2c2d196ea3d0396a6/marcsaric}, description = {MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data - PubMed}, doi = {10.1186/s13059-016-1029-6}, interhash = {5334d77e70e667f2b90b94d1cf2968e9}, intrahash = {6f006628d206d1b2c2d196ea3d0396a6}, journal = {Genome Biol}, keywords = {cancer-research exome fulltext gdc pipeline shouldread software variant-calling wxs}, month = {08}, number = 1, pages = {178-178}, pmid = {27557938}, timestamp = {2020-08-02T20:43:41.000+0200}, title = {MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data}, url = {https://pubmed.ncbi.nlm.nih.gov/27557938/}, volume = 17, year = 2016 }