ena-STUDY-NETHERLANDS CANCER INSTITUTE-11-08-2014-14:57:55:377-215
Mouse SCLC tumors were analysed by whole exome sequencing and used to obtain DNA copy number profiles using ENCODER.
Current methods for the detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data use the depth of coverage of captured exons only. Accurate CNA determination is complicated by the uneven distribution of exons throughout the genome and non-uniform sequence capture. We developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems by exploiting the ‘off-target’ sequence reads. ENCODER allows the extraction of uniformly distributed copy number information. In addition, ENCODER outperforms methods based on exonic sequence read counts, particularly on samples of low quality.  The sample in this ENA study were part of the samples used to validate ENCODER. Matching NimbleGen array data was deposited in GEO (GSE60254).
Current methods for the detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data use the depth of coverage of captured exons only. Accurate CNA determination is complicated by the uneven distribution of exons throughout the genome and non-uniform sequence capture. We developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems by exploiting the ‘off-target’ sequence reads. ENCODER allows the extraction of uniformly distributed copy number information. In addition, ENCODER outperforms methods based on exonic sequence read counts, particularly on samples of low quality.  The sample in this ENA study were part of the samples used to validate ENCODER. Matching NimbleGen array data was deposited in GEO (GSE60254).