Reference-unbiased copy number variant analysis using CGH microarrays

Abstract

Comparative genomic hybridization (CGH) microarrays have been used to determine copy number variations (CNVs) and their effects on complex diseases. Detection of absolute CNVs independent of genomic variants of an arbitrary reference sample has been a critical issue in CGH array experiments. Whole genome analysis using massively parallel sequencing with multiple ultra-high resolution CGH arrays provides an opportunity to catalog highly accurate genomic variants of the reference DNA (NA10851). Using information on variants, we developed a new method, the CGH array reference-free algorithm (CARA), which can determine reference-unbiased absolute CNVs from any CGH array platform. The algorithm enables the removal and rescue of false positive and false negative CNVs, respectively, which appear due to the effects of genomic variants of the reference sample in raw CGH array experiments. We found that the CARA remarkably enhanced the accuracy of CGH array in determining absolute CNVs. Our method thus provides a new approach to interpret CGH array data for personalized medicine.