title: Quantitative analysis of differences in copy numbers using read depth obtained from PCR-enriched samples and controls.
abstract: BACKGROUND
  Next-generation sequencing (NGS) is rapidly becoming common practice in clinical diagnostics and cancer research. In addition to the detection of single nucleotide variants (SNVs), information on copy number variants (CNVs) is of great interest. Several algorithms exist to detect CNVs by analyzing whole genome sequencing data or data from samples enriched by hybridization-capture. PCR-enriched amplicon-sequencing data have special characteristics that have been taken into account by only one publicly available algorithm so far.
  
  
  RESULTS
  We describe a new algorithm named quandico to detect copy number differences based on NGS data generated following PCR-enrichment. A weighted t-test statistic was applied to calculate probabilities (p-values) of copy number changes. We assessed the performance of the method using sequencing reads generated from reference DNA with known CNVs, and we were able to detect these variants with 98.6% sensitivity and 98.5% specificity which is significantly better than another recently described method for amplicon sequencing. The source code (R-package) of quandico is licensed under the GPLv3 and it is available at https://github.com/reineckef/quandico .
  
  
  CONCLUSIONS
  We demonstrated that our new algorithm is suitable to call copy number changes using data from PCR-enriched samples with high sensitivity and specificity even for single copy differences.
authors.affiliation: Bioinformatics Assay Design & Analysis, QIAGEN GmbH, Max-Volmer-Straße 4, Hilden, 40724, Germany. frank.reinecke@qiagen.com.
authors.forename: Frank
authors.initials: F
authors.lastname: Reinecke
authors.affiliation: Bioinformatics Assay Design & Analysis, QIAGEN Sciences Inc., 6951 Executive Way, Frederick MD, 21703, USA. ravi.vijayasatya@qiagen.com.
authors.forename: Ravi Vijaya
authors.initials: RV
authors.lastname: Satya
authors.affiliation: Bioinformatics Assay Design & Analysis, QIAGEN Sciences Inc., 6951 Executive Way, Frederick MD, 21703, USA. john.dicarlo@qiagen.com.
authors.forename: John
authors.initials: J
authors.lastname: DiCarlo
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D056915:DNA Copy Number Variations; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D016133:Polymerase Chain Reaction / Q000379:methods*; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*