title: Comparison of somatic mutation calling methods in amplicon and whole exome sequence data.
abstract: BACKGROUND
  High-throughput sequencing is rapidly becoming common practice in clinical diagnosis and cancer research. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal DNA sequencing. Although numerous studies have compared the performance of various algorithms on exome data, there has not yet been a systematic evaluation using PCR-enriched amplicon data with a range of variant allele fractions. The recently developed gold standard variant set for the reference individual NA12878 by the NIST-led "Genome in a Bottle" Consortium (NIST-GIAB) provides a good resource to evaluate admixtures with various SNV fractions.
  
  
  RESULTS
  Using the NIST-GIAB gold standard, we compared the performance of five popular somatic SNV calling algorithms (GATK UnifiedGenotyper followed by simple subtraction, MuTect, Strelka, SomaticSniper and VarScan2) for matched tumor-normal amplicon and exome sequencing data.
  
  
  CONCLUSIONS
  We demonstrated that the five commonly used somatic SNV calling methods are applicable to both targeted amplicon and exome sequencing data. However, the sensitivities of these methods vary based on the allelic fraction of the mutation in the tumor sample. Our analysis can assist researchers in choosing a somatic SNV calling method suitable for their specific needs.
authors.forename: Huilei
authors.initials: H
authors.lastname: Xu
authors.forename: John
authors.initials: J
authors.lastname: DiCarlo
authors.forename: Ravi Vijaya
authors.initials: RV
authors.lastname: Satya
authors.forename: Quan
authors.initials: Q
authors.lastname: Peng
authors.affiliation: Research and Foundation Department, QIAGEN Sciences, Inc,, Frederick, MD, USA. yexun.wang@qiagen.com.
authors.forename: Yexun
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030561:Databases, Nucleic Acid; D059472:Exome; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009154:Mutation; D017354:Point Mutation; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012984:Software