OutLyzer: software for extracting low-allele-frequency tumor mutations from sequencing background noise in clinical practice

// Etienne Muller 1, 2 , Nicolas Goardon 1 , Baptiste Brault 1 , Antoine Rousselin 1 , Germain Paimparay 1 , Angelina Legros 1 , Robin Fouillet 1 , Olivia Bruet 1 , Aurore Tranchant 1 , Florian Domin 1 , Chankannira San 1 , Celine Quesnelle 1 , Thierry Frebourg 2, 3, 4 , Agathe Ricou 1 , Sophie Krieger 1, 2, 5 , Dominique Vaur 1, 2 , Laurent Castera 1, 2 1 Department of Cancer Biology and Genetics, CCC Francois Baclesse, Genomic and Personalized Medicine in Cancer and Neurological Disorders Unit, Caen, France 2 Inserm U1079, Genomic and Personalized Medicine in Cancer and Neurological Disorders Unit, Rouen, France 3 Genetic Department, Rouen University Hospital, Genomic and Personalized Medicine in Cancer and Neurological Disorders Unit, Rouen, France 4 Rouen University, France 5 Caen University, France Correspondence to: Laurent Castera, email: l.castera@baclesse.unicancer.fr Keywords: variant-caller, somatic mutation, bioinformatics, oncology, precision medicine Received: May 26, 2016      Accepted: October 11, 2016      Published: November 04, 2016 ABSTRACT Highlighting tumoral mutations is a key step in oncology for personalizing care. Considering the genetic heterogeneity in a tumor, software used for detecting mutations should clearly distinguish real tumor events of interest that could be predictive markers for personalized medicine from false positives. OutLyzer is a new variant-caller designed for the specific and sensitive detection of mutations for research and diagnostic purposes. It is based on statistic and local evaluation of sequencing background noise to highlight potential true positive variants. 130 previously genotyped patients were sequenced after enrichment by capturing the exons of 22 genes. Sequencing data were analyzed by HaplotypeCaller, LofreqStar, Varscan2 and OutLyzer. OutLyzer had the best sensitivity and specificity with a fixed limit of detection for all tools of 1% for SNVs and 2% for Indels. OutLyzer is a useful tool for detecting mutations of interest in tumors including low allele-frequency mutations, and could be adopted in standard practice for delivering targeted therapies in cancer treatment.