Smoothed functional principal component analysis for testing association of the entire allelic spectrum of genetic variation

European Journal of Human Genetics

Volumn 21, Issue 2, 2013, Pages 217-224

  Luo, Li ^a   Zhu, Yun ^b   Xiong, Momiao ^b  

^a UNIVERSITY OF NEW MEXICO SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF TEXAS SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

association studies; next generation sequencing; rare variants; Smoothed functional principal component analysis

Indexed keywords

ALLELE; ANGPTL4 GENE; ARTICLE; COLLAPSING METHOD; COMBINED MULTIVARIATE AND COLLAPSING METHOD; FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS DISCRETIZATION; FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS DISCRETIZATION FOURIER EXPANSION; GENE; GENE FREQUENCY; GENE SEQUENCE; GENERALIZED T2; GENETIC ASSOCIATION; GENETIC VARIABILITY; HUMAN; MULTIVARIATE PRINCIPAL COMPONENT ANALYSIS; NULL HYPOTHESIS; PHENOTYPE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SCHIZOPHRENIA; SIMULATION; SMOOTHED FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS; SMOOTHED FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS DISCRETIZATION; SMOOTHED FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS FOURIER EXPANSION; VARIABLE THRESHOLD METHOD; WEIGHTED SUM STATISTIC;

ALLELES; ANGIOPOIETINS; DATA INTERPRETATION, STATISTICAL; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HEART DISEASES; HUMANS; PRINCIPAL COMPONENT ANALYSIS; SCHIZOPHRENIA;

EID: 84872486441     PISSN: 10184813     EISSN: 14765438     Source Type: Journal    
DOI: 10.1038/ejhg.2012.141     Document Type: Article

References (28)

1. Rakyan VK, Down TA, Balding DJ et al. Epigenome-wide association studies for common human diseases. Nat Rev Genet 2011; 12: 529-541.
2. Neale BM, Rivas MA, Voight BF et al. Testing for an unusual distribution of rare variants. PLoS Genet 2011; 7: e1001322.
3. Bansal V, Libiger O, Torkamani A et al. Statistical analysis strategies for association studies involving rare variants. Nat RevGenet 2010; ll: 773-785.
4. Pool JE, Hellmann I, Jensen JD et al. Population genetic inference from genomic sequence variation. Genome Res 2010; 20: 291-300.
5. Bacanu SA, Nelson MR, Whittaker JC: Comparison of methods and sampling designs to test for association between rare variants and quantitative traits. Genet Epidemiol 2011; 35: 226-235.
6. Shi Y, Rao Y: China's research culture. Science 2010; 329: 1128.
7. Li Y, Byrnes AE, Li M: To identify associations with rare variants, just WHaIT: weighted haplotype and imputation-based tests. Am J Hum Genet 2010; 87: 728-735.
8. Li B, Leal SM: Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet 2008; 83: 311-321.
9. Madsen BE, Browning SR: A groupwise association test for rare mutations using a weighted sum statistic PLoS Genet 2009; 5: e1000384.
10. Price AL, Kryukov GV, de Bakker PI et al. Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet 2010; 86: 832-838.
11. KingCR, Rathouz PJ, NicolaeDL:Anevolutionary frame work for association testing in resequencing studies. PLoS Genet 2010; 6: e1001202.
12. Yi N, Zhi D: Bayesian analysis of rare variants in genetic association studies. Genet Epidemiol 2011; 35: 57-69.
13. Han F, Pan W.: Adata-adaptivesum test for diseaseassociation with multiplecommon or rare variants. Hum Hered 2010; 70: 42-54.
14. Ionita-Laza I, Buxbaum JD, Laird NM et al. A new testing strategy to identify rare variants with either risk or protective effect on disease. PLoS Genet 2011; 7: e1001289.
15. Hoffmann TJ, Marini NJ, Witte JS: Comprehensive approach to analyzing rare genetic variants. PLoS One 2010; 5: e13584.
16. Liu DJ, Leal SM: A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions. PLoS Genet 2010; 6: e1001156.
17. Mukhopadhyay I, Feingold E, Weeks DE et al. Association tests using kernel-based measures of multi-locus genotype similarity between individuals. Genet Epidemiol 2010; 34: 213-221.
18. Luo L, Boerwinkle E, Xiong M: Association studies for next-generation sequencing. Genome Res 2011; 21: 1099-1108.
19. Xiong M, Zhao J, Boerwinkle E: Generalized T2 test for genome association studies. Am J Hum Genet. 2002; 70: 1257-1268.
20. Romeo S, Pennacchio LA, Fu Y et al. Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increaseHDL. Nat Genet2007; 39: 513-516.
21. Ramsay JO, Silverman BW: Functional Data Analysis, Second Edition. New York: Springer, 2005.
22. Hudson RR: Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics 2002; 18: 337-338.
23. Wu MC, Lee S, Cai T et al. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 2011; 89: 82-93.
24. Peng G, Luo L, Siu H etal: Geneand pathway-based second-wave analysis of genome-wide association studies. Eur J Hum Genet 2010; 18: 111-117.
25. Zhao T, Liu Y, Wang P etal: Positive association between the PDLIM5 geneand bipolar disorder in the Chinese Han population. J Psychiatry Neurosci 2009; 34: 199-204.
26. Shimada M, Miyagawa T, Kawashima M et al. An approach based on a genome-wide association study reveals candidate loci for narcolepsy. Hum Genet 2010; 128: 433-441.
27. Kim JM, Lee KH, Jeon YJ et al. Identification of genes related to Parkinson's disease using expressed sequence tags. DNA Res 2006; 13: 275-286.
28. Singh RR, Kumar R: MTA family of transcriptional metaregulators in mammary gland morphogenesis and breast cancer. J. Mammary Gland Biol. Neoplasia 2007; 12: 115-125.