Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2

Description:

EXCAVATOR2 is a read count (RC) based tool that exploits all the reads produced by Whole Exome Sequencing (WES) and Targeted Sequencing (TS) experiments to detect Copy Number Variants (CNV) with a genome-wide resolution. Copy Number Variants are structural rearrangements involving DNA segments of at least 50bp that can be present with an altered copy number compared to the reference genome. They are one of the main sources of genomic variation in humans contributing to phenotypic variation but are also associated with many classes of diseases, from neurological disorders to cancer. Various computational methods have been developed for the detection of CNVs starting from NGS data are based on the read count (RC) approach. EXCAVATOR2 exploits all reads produced by targeted sequencing experiments using probes enrichment kits and, combining signals from In- and Off-Target, it enhances the identification of genomic CNVs, particularly in exon-rich regions, and to be more accurate in breakpoints detection. It can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing studies with best performance, and so maximizing the utility of exome sequencing data in genetic and cancer studies. Lastly, it is of particular interest that all WES/TS experiments can be re-analysed using our method with the beneficial effect to identify CNVs affecting non-coding genomic regions. We are investigating the feasibility of our method on cancer genomic data, with specific focus on tumour heterogeneity and classification for clinical purpose, and on the identification of non-coding alterations associated with mendelian disorders.

Source code and datasets

The source code, supplementary files and user manual are available at the Sourceforgenet repository

Citation

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M. Elena Renda