single-cell copy number variation detection单细胞拷贝数变异检测.pdf

Cheng et al. Genome Biology 2011, 12:R80 /content/12/8/R80 METHOD Open Access Single-cell copy number variation detection 1,2 3 1,2 3 3 1,2* Jiqiu Cheng , Evelyne Vanneste , Peter Konings , Thierry Voet , Joris R Vermeesch and Yves Moreau Abstract Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data. Background CGHnormaliter have been developed for array CGH Array analysis of single-cell copy number variations data [10,11]. Poplowess attempts to separate normal (CNVs) is a recently developed experimental technique from aberrant probes using k-means clustering and for the detection of chromosomal rearrangements in applies the loess normalization based on the largest single cells [1-4]. Two-color single-cell array compara- group of probes, whereas CGHnormaliter combines a tive genomic hybridization (CGH) assays the copy segmentation a