Gene Copy Number Analysis for Family Data Using Semiparametric Copula Model

Overview

Journal Bioinform Biol Insights

Publisher Sage Publications

Specialty Biology

Date 2009 Oct 9

PMID 19812787

Citations 1

Authors

Ao Yuan

Guanjie Chen

Zhong-Cheng Zhou

George Bonney

Charles Rotimi

Affiliations

Soon will be listed here.

Abstract

Gene copy number changes are common characteristics of many genetic disorders. A new technology, array comparative genomic hybridization (a-CGH), is widely used today to screen for gains and losses in cancers and other genetic diseases with high resolution at the genome level or for specific chromosomal region. Statistical methods for analyzing such a-CGH data have been developed. However, most of the existing methods are for unrelated individual data and the results from them provide explanation for horizontal variations in copy number changes. It is potentially meaningful to develop a statistical method that will allow for the analysis of family data to investigate the vertical kinship effects as well. Here we consider a semiparametric model based on clustering method in which the marginal distributions are estimated nonparametrically, and the familial dependence structure is modeled by copula. The model is illustrated and evaluated using simulated data. Our results show that the proposed method is more robust than the commonly used multivariate normal model. Finally, we demonstrated the utility of our method using a real dataset.

Citing Articles

Bayesian Frequentist hybrid Model wth Application to the Analysis of Gene Copy Number Changes.

Yuan A, Chen G, Xiong J, He W, Rotimi C J Appl Stat. 2013; 38(5):987-1005.

PMID: 24014930 PMC: 3762327. DOI: 10.1080/02664761003692449.

References

Picard F, Robin S, Lavielle M, Vaisse C, Daudin J . A statistical approach for array CGH data analysis. BMC Bioinformatics. 2005; 6:27. PMC: 549559. DOI: 10.1186/1471-2105-6-27. View

Gonzalez E, Kulkarni H, Bolivar H, Mangano A, Sanchez R, Catano G . The influence of CCL3L1 gene-containing segmental duplications on HIV-1/AIDS susceptibility. Science. 2005; 307(5714):1434-40. DOI: 10.1126/science.1101160. View

Daruwala R, Rudra A, Ostrer H, Lucito R, Wigler M, Mishra B . A versatile statistical analysis algorithm to detect genome copy number variation. Proc Natl Acad Sci U S A. 2004; 101(46):16292-7. PMC: 528962. DOI: 10.1073/pnas.0407247101. View

Eilers P, de Menezes R . Quantile smoothing of array CGH data. Bioinformatics. 2004; 21(7):1146-53. DOI: 10.1093/bioinformatics/bti148. View

Pugh T, Delaney A, Farnoud N, Flibotte S, Griffith M, Li H . Impact of whole genome amplification on analysis of copy number variants. Nucleic Acids Res. 2008; 36(13):e80. PMC: 2490749. DOI: 10.1093/nar/gkn378. View

Snijders A, Nowak N, Segraves R, Blackwood S, Brown N, Conroy J . Assembly of microarrays for genome-wide measurement of DNA copy number. Nat Genet. 2001; 29(3):263-4. DOI: 10.1038/ng754. View

Pollack J, Sorlie T, Perou C, Rees C, Jeffrey S, Lonning P . Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci U S A. 2002; 99(20):12963-8. PMC: 130569. DOI: 10.1073/pnas.162471999. View

Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D . High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 1998; 20(2):207-11. DOI: 10.1038/2524. View

Cappuzzo F, Varella-Garcia M, Shigematsu H, Domenichini I, Bartolini S, Ceresoli G . Increased HER2 gene copy number is associated with response to gefitinib therapy in epidermal growth factor receptor-positive non-small-cell lung cancer patients. J Clin Oncol. 2005; 23(22):5007-18. DOI: 10.1200/JCO.2005.09.111. View

10.

Cheng C, Kimmel R, Neiman P, Zhao L . Array rank order regression analysis for the detection of gene copy-number changes in human cancer. Genomics. 2003; 82(2):122-9. DOI: 10.1016/s0888-7543(03)00122-8. View

11.

Freeman J, Perry G, Feuk L, Redon R, McCarroll S, Altshuler D . Copy number variation: new insights in genome diversity. Genome Res. 2006; 16(8):949-61. DOI: 10.1101/gr.3677206. View

12.

Yuan A, He W . Semiparametric clustering method for microarray data analysis. J Bioinform Comput Biol. 2008; 6(2):261-82. DOI: 10.1142/s021972000800345x. View

13.

Morley M, Molony C, Weber T, Devlin J, Ewens K, Spielman R . Genetic analysis of genome-wide variation in human gene expression. Nature. 2004; 430(7001):743-7. PMC: 2966974. DOI: 10.1038/nature02797. View

14.

Lampel S, Stilgenbauer S, Nickolenko J, Benner A, Dohner H, Cremer T . Matrix-based comparative genomic hybridization: biochips to screen for genomic imbalances. Genes Chromosomes Cancer. 1997; 20(4):399-407. View

15.

Broet P, Richardson S . Detection of gene copy number changes in CGH microarrays using a spatially correlated mixture model. Bioinformatics. 2006; 22(8):911-8. DOI: 10.1093/bioinformatics/btl035. View

16.

Jong K, Marchiori E, Meijer G, Vaart A, Ylstra B . Breakpoint identification and smoothing of array comparative genomic hybridization data. Bioinformatics. 2004; 20(18):3636-7. DOI: 10.1093/bioinformatics/bth355. View

17.

Kallioniemi A, Kallioniemi O, Sudar D, Rutovitz D, Gray J, Waldman F . Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science. 1992; 258(5083):818-21. DOI: 10.1126/science.1359641. View

18.

Hodgson G, Hager J, Volik S, Hariono S, Wernick M, Moore D . Genome scanning with array CGH delineates regional alterations in mouse islet carcinomas. Nat Genet. 2001; 29(4):459-64. DOI: 10.1038/ng771. View

19.

Eisen M, Spellman P, Brown P, Botstein D . Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A. 1998; 95(25):14863-8. PMC: 24541. DOI: 10.1073/pnas.95.25.14863. View

20.

Barash Y, Friedman N . Context-specific Bayesian clustering for gene expression data. J Comput Biol. 2002; 9(2):169-91. DOI: 10.1089/10665270252935403. View