Inference of chromosome-specific copy numbers using population haplotypes

BMC Bioinformatics

Methodology Article

Yao-Ting Huang¹  Min-Han Wu¹ 

[1] Department of Computer Science and Information Engineering, National Chung Cheng University, 621, Chia-Yi, Taiwan;

关键词: Linkage Disequilibrium;    Constraint Satisfaction Problem;    Linkage Disequilibrium Structure;    Haplotype Pair;    Hard Edge;   

DOI  :  10.1186/1471-2105-12-194

 received in 2010-10-31, accepted in 2011-05-24,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundUsing microarray and sequencing platforms, a large number of copy number variations (CNVs) have been identified in humans. In practice, because our human genome is a diploid, these platforms are limited to or more accurate for detecting total copy numbers rather than chromosome-specific copy numbers at each of the two homologous chromosomes. Nevertheless, the analysis of linkage disequilibrium (LD) between CNVs and SNPs indicates that distinct copy numbers often sit on their own background haplotypes.ResultsWe propose new computational models for inferring chromosome-specific copy numbers by distinguishing background haplotypes of each copy number. The formulated problems are shown to be NP-hard and approximation/heuristic algorithms are developed. Simulation indicates that our method is accurate and outperforms the existing approach. By testing the program in 60 parent-offspring trios, the inferred chromosome-specific copy numbers are highly consistent with the law of Mendelian inheritance. The distributions of copy numbers at chromosomal level are provided for 270 individuals in three HapMap panels.ConclusionsThe estimation of chromosome-specific copy numbers using microarray or sequencing platforms was often confounded by a number of factors. This study showed that the integration of background haplotypes is able to improve the accuracies of copy number estimation at chromosome level, especially for the CNVs having strong LD with SNPs in proximity.

【 授权许可】

CC BY   
© Huang and Wu; licensee BioMed Central Ltd. 2011