title: Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller.
abstract: Detection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models.
  
  
  
  We present here a highly efficient, simple and scalable enrichment protocol that integrates molecular barcodes in multiplex PCR amplification. In addition, we developed smCounter, an open source, generic, barcode-aware variant caller based on a Bayesian probabilistic model. smCounter was optimized and benchmarked on two independent read sets with SNVs and indels at 5 and 1% allele fractions. Variants were called with very good sensitivity and specificity within coding regions.
  
  
  
  We demonstrated that we can accurately detect somatic mutations with allele fractions as low as 1% in coding regions using our enrichment protocol and variant caller.
authors.affiliation: Life Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA. chang.xu@qiagen.com.
authors.forename: Chang
authors.initials: C
authors.lastname: Xu
authors.affiliation: Life Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
authors.forename: Mohammad R
authors.initials: MR
authors.lastname: Nezami Ranjbar
authors.affiliation: Life Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Wu
authors.affiliation: Life Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
authors.forename: John
authors.initials: J
authors.lastname: DiCarlo
authors.affiliation: Life Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA. yexun.wang@qiagen.com.
authors.forename: Yexun
authors.identifier: 0000-0003-0362-1892
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000483:Alleles; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D058893:DNA Barcoding, Taxonomic; D005787:Gene Frequency; D014644:Genetic Variation; D015233:Models, Statistical; D060885:Multiplex Polymerase Chain Reaction; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Molecular barcode; PCR enrichment; Statistical model; Variant caller