Copy number alterations (CNA) are common events occurring in leukaemias and solid tumors. 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. Among them, whole-exome sequencing has been extensively used in the last few years to analyze the coding regions of cancer genomes in order to detect the presence of somatic variants. 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. By using the exome reads to generate a map of all the heterozygous positions in the control sample and by matching them to the corresponding case, exome sequencing can be also used to co-detect the presence of allelic imbalance (AI), coupling CNA data with LOH/AI information.
Unfortunately, the availability of user-friendly bioinformatics tools dedicated to the coupled CNA/AI 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/AI-coupled analysis of exome sequencing reads.