Modeling genetic inheritance of copy number variations.
Copy number variations (CNVs) are being used as genetic markers or functional candidates in gene-mapping studies. However, unlike single nucleotide polymorphism or microsatellite genotyping techniques, most CNV detection methods are limited to detecting total copy numbers, rather than copy number in each of the two homologous chromosomes. To address this issue, we developed a statistical framework for intensity-based CNV detection platforms using family data. Our algorithm identifies CNVs for a family simultaneously, thus avoiding the generation of calls with Mendelian inconsistency while maintaining the ability to detect de novo CNVs. Applications to simulated data and real data indicate that our method significantly improves both call rates and accuracy of boundary inference, compared to existing approaches. We further illustrate the use of Mendelian inheritance to infer SNP allele compositions in each of the two homologous chromosomes in CNV regions using real data. Finally, we applied our method to a set of families genotyped using both the Illumina HumanHap550 and Affymetrix genome-wide 5.0 arrays to demonstrate its performance on both inherited and de novo CNVs. In conclusion, our method produces accurate CNV calls, gives probabilistic estimates of CNV transmission and builds a solid foundation for the development of linkage and association tests utilizing CNVs.
Wang
Kai
K
Department of Genetics, Division of Human Genetics, Center for Applied Genomics, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA. wangk@chop.edu
Chen
Zhen
Z
Tadesse
Mahlet G
MG
Glessner
Joseph
J
Grant
Struan F A
SF
Hakonarson
Hakon
H
Bucan
Maja
M
Li
Mingyao
M
D000465:Algorithms; D002877:Chromosomes, Human / Q000737:chemistry*; D003198:Computer Simulation; D018628:Gene Dosage; D014644:Genetic Variation; D015894:Genome, Human; D023281:Genomics / Q000379:methods; D006801:Humans; D040582:Inheritance Patterns; D008390:Markov Chains; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide