[HTML][HTML] Accurate and exact CNV identification from targeted high-throughput sequence data

AS Nord, M Lee, MC King, T Walsh - BMC genomics, 2011 - Springer
BMC genomics, 2011Springer
Background Massively parallel sequencing of barcoded DNA samples significantly
increases screening efficiency for clinically important genes. Short read aligners are well
suited to single nucleotide and indel detection. However, methods for CNV detection from
targeted enrichment are lacking. We present a method combining coverage with map
information for the identification of deletions and duplications in targeted sequence data.
Results Sequencing data is first scanned for gains and losses using a comparison of …
Background
Massively parallel sequencing of barcoded DNA samples significantly increases screening efficiency for clinically important genes. Short read aligners are well suited to single nucleotide and indel detection. However, methods for CNV detection from targeted enrichment are lacking. We present a method combining coverage with map information for the identification of deletions and duplications in targeted sequence data.
Results
Sequencing data is first scanned for gains and losses using a comparison of normalized coverage data between samples. CNV calls are confirmed by testing for a signature of sequences that span the CNV breakpoint. With our method, CNVs can be identified regardless of whether breakpoints are within regions targeted for sequencing. For CNVs where at least one breakpoint is within targeted sequence, exact CNV breakpoints can be identified. In a test data set of 96 subjects sequenced across ~1 Mb genomic sequence using multiplexing technology, our method detected mutations as small as 31 bp, predicted quantitative copy count, and had a low false-positive rate.
Conclusions
Application of this method allows for identification of gains and losses in targeted sequence data, providing comprehensive mutation screening when combined with a short read aligner.
Springer