title: Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2.
abstract: Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/.
authors: Laboratory of Integrative Systems Medicine (LISM), Institute of Informatics and Telematics and Institute of Clinical Physiology, National Research Council, Pisa, Italy romina.daurizio@gmail.com.
authors: Romina
authors: R
authors: D'Aurizio
authors: Medical Genetics Unit, Sant'Orsola Malpighi Polyclinic, Bologna, Italy.
authors: Tommaso
authors: T
authors: Pippucci
authors: Department of Computer Science, University of Pisa, Pisa, Italy.
authors: Lorenzo
authors: L
authors: Tattini
authors: Department of Experimental and Clinical Medicine, University of Florence, Florence.
authors: Betti
authors: B
authors: Giusti
authors: Laboratory of Integrative Systems Medicine (LISM), Institute of Informatics and Telematics and Institute of Clinical Physiology, National Research Council, Pisa, Italy.
authors: Marco
authors: M
authors: Pellegrini
authors: Department of Experimental and Clinical Medicine, University of Florence, Florence albertomagi@gmail.com.
authors: Alberto
authors: A
authors: Magi
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D056915:DNA Copy Number Variations; D059472:Exome; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D015203:Reproducibility of Results; D012984:Software; D064878:Web Browser