Abstract 5144: Comparative Exonic Quantification analyzer (CEQer): a graphical, event-driven tool for copy number and allelic imbalance detection from whole-exome sequencing data.

Copy number alterations (CNA) are common events occurring in leukaemias and solid tumors. Comparative Genome Hybridization (CGH) is actually the gold standard technique to analyze CNA, however CGH analyses require dedicated instruments and it is able to perform only low resolution Loss of Heterozygosity (LOH) analyses. Recently, the development of high-throughput sequencing instruments able to generate hundreds of Gigabases per run allowed the development of completely new approaches to the analysis of cancer genomes. By using exome reads as digital counters and by performing a case/control normalization to take into account differences in the enrichment efficiency, it is possible to detect both negative and positive CNA by identifying the associated decrease/increase in the exonic read counts. Unfortunately, the availability of user-friendly bioinformatics tools dedicated to the coupled CNA/AI (allelic imbalance) analysis of exome sequencing data is very limited. To overcome this limitation we developed CEQer (Comparative Exome Quantification analyzer), a new graphical, event-driven tool for CNA/allelic-unbalance coupled analysis of exome sequencing data. By using case-control matched exome data, CEQer performs a comparative digital exonic quantification to generate CNA data and couples this information with exome-wide LOH and AI detection. These data are used to build mixed statistical/heuristic models allowing the identification of CNA/AI events. CEQer runs on standard 32 or 64 bit desktop/notebook PC and accepts the most widely used alignment/pileup file formats (Pileup/BED, SAM and BAM) as input. CEQer requires no a priori bioinformatics or scripting knowledge, being graphical and event driven. It manages either single or multiple jobs by using a dedicated batch tool and generates interactive graphical views as well as textual reports as output. To test our tool, we initially used in silico generated data with progressively increasing background noise, then we performed whole-exome sequencing from 20 leukemic specimens and corresponding matched controls and we analyzed the results using CEQer. Taken globally, these analyses showed that the combined use of comparative digital exon quantification and LOH/AI allows to generate very accurate CNA data, when compared to standard CGH. Therefore, we propose CEQer as an efficient, robust and user-friendly graphical tool for the identification of CNA in the context of whole-exome sequencing data. Citation Format: Rocco Piazza, Vera Magistroni, Alessandra Pirola, Sara Redaelli, Roberta Spinelli, Serena Redaelli, Marta Galbiati, Simona Valletta, Giovanni Giudici, Giovanni Cazzaniga, Carlo Gambacorti Passerini. Comparative Exonic Quantification analyzer (CEQer): a graphical, event-driven tool for copy number and allelic imbalance detection from whole-exome sequencing data. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5144. doi:10.1158/1538-7445.AM2013-5144