MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data
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), Mu...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Online |
| Language: | English |
| Published: |
BioMed Central
2016
|
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995747/ |