CEQer: A Graphical Tool for Copy Number and Allelic Imbalance Detection from Whole-Exome Sequencing Data |
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Authors: | Rocco Piazza Vera Magistroni Alessandra Pirola Sara Redaelli Roberta Spinelli Serena Redaelli Marta Galbiati Simona Valletta Giovanni Giudici Giovanni Cazzaniga Carlo Gambacorti-Passerini |
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Affiliation: | 1. Department of Health Sciences, University of Milano-Bicocca, Monza, Italy.; 2. Department of Neurosciences and Biomedical Technologies, University of Milano-Bicocca, Monza, Italy.; 3. Tettamanti Research Center, University of Milano-Bicocca, San Gerardo Hospital, Monza, Italy.; Institut Jacques Monod, France, |
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Abstract: | 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 CNAs; however, CGH analysis requires dedicated instruments and is able to perform only low resolution Loss of Heterozygosity (LOH) analyses. Here we present CEQer (Comparative Exome Quantification analyzer), a new graphical, event-driven tool for CNA/allelic-imbalance (AI) 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 allelic imbalance detection. This data is used to build mixed statistical/heuristic models allowing the identification of CNA/AI events. To test our tool, we initially used in silico generated data, 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 generating very accurate CNA data. Therefore, we propose CEQer as an efficient, robust and user-friendly graphical tool for the identification of CNA/AI in the context of whole-exome sequencing data. |
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