A unified sparse representation for sequence variant identification for complex traits

Genetic Epidemiology

Volumn 38, Issue 8, 2014, Pages 671-679

  Cao, Shaolong ^a,b   Qin, Huaizhen ^a,b   Deng, Hong Wen ^a,b   Wang, Yu Ping ^a,b  

^a TULANE UNIVERSITY   (United States)

^b TULANE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Mexican Americans; Population structure; Prior biological information; Relatedness; Sparse regression

Indexed keywords

VASCULOTROPIN RECEPTOR 1; VASCULOTROPIN RECEPTOR 2;

ALGORITHM; ALLELE; ARTICLE; COMPLEX TRAIT; DIASTOLIC BLOOD PRESSURE; DNA SEQUENCE; GENE FREQUENCY; GENETIC ASSOCIATION; GENETIC SUSCEPTIBILITY; GENETIC TRAIT; GENETIC VARIABILITY; GENOTYPE; HAPLOTYPE; HERITABILITY; HUMAN; HYPERTENSION; MATHEMATICAL PARAMETERS; MEXICAN AMERICAN; NEXT GENERATION SEQUENCING; NUCLEAR FAMILY; PEDIGREE; PHENOTYPE; POPULATION STRUCTURE; SINGLE NUCLEOTIDE POLYMORPHISM; SYSTOLIC BLOOD PRESSURE; UNIFIED SPARSE REGRESSION; BIOLOGICAL MODEL; GENE LOCUS; PROCEDURES; REGRESSION ANALYSIS;

ALGORITHMS; GENETIC LOCI; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MODELS, GENETIC; REGRESSION ANALYSIS; SEQUENCE ANALYSIS, DNA;

EID: 84910642131     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21849     Document Type: Article

References (36)

1. Candes EJ, Tao T. 2005. Decoding by linear programming. IEEE Trans Inform Theory 51(12):4203-4215.
2. Cetin MC, Erar A. 2002. Variable selection with Akaike information criteria: a comparative study. Hacet J Math Stat 31:89-97.
3. Chen X, Ishwaran H. 2012. Random forests for genomic data analysis. Genomics 99(6):323-329.
4. Chen X, Xu F, Ye Y. 2010. Lower bound theory of nonzero entries in solutions of ℓ2-ℓp minimization. SIAM J Sci Comp 32(5):2832-2852.
5. Cho S, Kim K, Kim YJ, Lee JK, Cho YS, Lee JY, Han BG, Kim H, Ott J, Park T. 2010. Joint identification of multiple genetic variants via elastic-net variable selection in a genome-wide association analysis. Ann Hum Genet 74(5):416-428.
6. Dong C, Beecham A, Wang L, Blanton SH, Rundek T, Sacco RL. 2012. Follow-up association study of linkage regions reveals multiple candidate genes for carotid plaque in Dominicans. Atherosclerosis 223(1):177-183.
7. Dumitrescu D, Seck C, ten Freyhaus H, Gerhardt F, Erdmann E, Rosenkranz S. 2011. Fully reversible pulmonary arterial hypertension associated with dasatinib treatment for chronic myeloid leukaemia. Eur Respir J 38(1):218-220.
8. Fan J, Li R. 2001. Variable selection via nonconcave penalized likelihood and its oracle properties. J Am Stat Assoc 96(456):1348-1360.
9. Friedman J, Hastie T, Höfling H, Tibshirani R. 2007. Pathwise coordinate optimization. Ann App Stat 1(2):302-332.
10. Friedman J, Hastie T, Tibshirani R. 2010. Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33(1):1-22.
11. Goldstein BA, Hubbard AE, Cutler A, Barcellos LF. 2010. An application of Random Forests to a genome-wide association dataset: methodological considerations & new findings. BMC Genet 11(1):11-49.
12. Guymer R, Cairns J, O'Day J. 1993. Benign intracranial hypertension in chronic myeloid leukemia. Aust NZ J Ophthalmol 21(3):181-185.
13. Hong H, Wang H, Liao H. 2013. Prehypertension is associated with increased carotid atherosclerotic plaque in the community population of Southern China. BMC Cardiovasc Disord 13(1):13-20.
14. Houben M, Louwman W, Tijssen C, Teepen J, Van Duijn C, Coebergh J. 2004. Hypertension as a risk factor for glioma? Evidence from a population-based study of comorbidity in glioma patients. Ann Oncol 15(8):1256-1260.
15. Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E. 2008. Efficient control of population structure in model organism association mapping. Genetics 178(3):1709-1723.
16. Lee S, Wu MC, Lin X. 2012. Optimal tests for rare variant effects in sequencing association studies. Biostatistics 13(4):762-775.
17. Mathieson I, McVean G. 2012. Differential confounding of rare and common variants in spatially structured populations. Nat Genet 44(3):243-246.
18. Meinshausen N, Bühlmann P. 2010. Stability selection. J R Stat Soc Ser B (Stat Method) 72(4):417-473.
19. Mendelsohn AR, Larrick J. 2013. Dietary modification of the microbiome affects risk for cardiovascular disease. Rejuvenation Res 16(3):241-244.
20. Meng L, Chen D, Yang Y, Zheng Y, Hui R. 2012. Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. J Hypertens 30(5):842-851.
21. Natarajan BK. 1995. Sparse approximate solutions to linear systems. SIAM J Comput 24(2):227-234.
22. Price AL, Zaitlen NA, Reich D, Patterson N. 2010. New approaches to population stratification in genome-wide association studies. Nat Rev Genet 11(7):459-463.
23. Qin H, Morris N, Kang SJ, Li M, Tayo B, Lyon H, Hirschhorn J, Cooper RS, Zhu X. 2010. Interrogating local population structure for fine mapping in genome-wide association studies. Bioinformatics 26(23):2961-2968.
24. Rao BD, Kreutz-Delgado K. 1999. An affine scaling methodology for best basis selection. IEEE Trans Signal Process 47(1):187-200.
25. Thompson E, Shaw R. 1990. Pedigree analysis for quantitative traits: variance components without matrix inversion. Biometrics 46:399-413.
26. Thornton T, Tang H, Hoffmann TJ, Ochs-Balcom HM, Caan BJ, Risch N. 2012. Estimating kinship in admixed populations. Am J Hum Genet 91(1):122-138.
27. Tripodi G, Valtorta F, Torielli L, Chieregatti E, Salardi S, Trusolino L, Menegon A, Ferrari P, Marchisio P-C, Bianchi G. 1996. Hypertension-associated point mutations in the adducin alpha and beta subunits affect actin cytoskeleton and ion transport. J Clin Invest 97(12):2815-2822.
28. Wu TT, Chen YF, Hastie T, Sobel E, Lange K. 2009. Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics 25(6):714-721.
29. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. 2011. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 89(1):82-93.
30. Xu Z-B, Guo H-L, Wang Y, Zhang H. 2012a. Representative of L1/2 regularization among Lq Lq Lq (0 < q ≤ 1) regularizations: an experimental study based on phase diagram. Acta Autom Sin 38(7):1225-1228.
31. Xu Z, Chang X, Xu F, Zhang H. 2012b. L1/2regularization: a thresholding representation theory and a fast solver. IEEE Trans Neural Netw Learn Syst 23(7):1013-1027.
32. Yi N, Liu N, Zhi D, Li J. 2011. Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects. PLoS Genet 7(12):e1002382.
33. Zhang C, Chen X. 2009. Smoothing projected gradient method and its application to stochastic linear complementarity problems. SIAM J Optim 20(2):627-649.
34. Zhou X, Stephens M. 2012. Genome-wide efficient mixed-model analysis for association studies. Nat Genet 44(7):821-824.
35. Zhou H, Sehl ME, Sinsheimer JS, Lange K. 2010. Association screening of common and rare genetic variants by penalized regression. Bioinformatics 26(19):2375-2382.
36. Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J R Stat Soc Ser B (Stat Method) 67(2):301-320.