Genotype imputation reference panel selection using maximal phylogenetic diversity

Genetics

Volumn 195, Issue 2, 2013, Pages 319-330

  Zhang, Peng ^a   Zhan, Xiaowei ^a   Rosenberg, Noah A ^c   Zöllner, Sebastian ^a,b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b UNIVERSITY OF MICHIGAN HEALTH SYSTEM   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPARATIVE STUDY; COST EFFECTIVENESS ANALYSIS; GENE FREQUENCY; GENE SEQUENCE; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOTYPE; GENOTYPE IMPUTATION; GENOTYPING TECHNIQUE; HUMAN; PHYLOGENOMICS; PHYLOGENY; PRIORITY JOURNAL;

COALESCENT; IMPUTATION; PHYLOGENETIC DIVERSITY; SEQUENCING; STUDY DESIGN;

GENE FREQUENCY; GENETIC VARIATION; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMAN GENOME PROJECT; HUMANS; PHYLOGENY; SOFTWARE;

EID: 84884921432     PISSN: 00166731     EISSN: 19432631     Source Type: Journal    
DOI: 10.1534/genetics.113.154591     Document Type: Article

References (34)

1. Atwell, S., Y. S. Huang, B. J. Vilhjalmsson, G. Willems, M. Horton et al., 2010 Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465: 627-631.
2. Atteson, K., 1999 The performance of neighbor-joining methods of phylogenetic reconstruction. Algorithmica 25: 251-278.
3. Badke, Y.M., R. O. Bates, C. W. Ernst, C. Schwab, J. Fix et al., 2013 Methods of tagSNP selection and other variables affecting imputation accuracy in swine. BMC Genet. 14: 1-14.
4. Brown, A. H. D., 1989 Core collections: a practical approach to genetic resources management. Genome 31: 818-824.
5. Faith, D. P., 1992 Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61: 1-10.
6. Frazer, K. A., D. G. Ballinger, D. R. Cox, D. A. Hinds, L. L. Stuve et al., 2007 A second generation human haplotype map of over 3.1 million SNPs. Nature 449: 851-861.
7. Fridley, B. L., G. Jenkins, M. E. Deyo-Svendsen, S. Hebbring, and R. Freimuth, 2010 Utilizing genotype imputation for the augmentation of sequence data. PLoS ONE 5: e11018.
8. Hao, K., E. Chudin, J. McElwee, and E. E. Schadt, 2009 Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies. BMC Genet. 10: 27.
9. Hickey, J.M., J. Crossa, R. Babu, and G. de los Campos, 2012 Factors affecting the accuracy of genotype imputation in populations from several maize breeding programs. Crop Sci. 52: 654-663.
10. Howie, B., C. Fuchsberger, M. Stephens, J. Marchini, and G. R. Abecasis, 2012 Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44: 955-959.
11. Huang, L., Y. Li, A. B. Singleton, J. A. Hardy, G. Abecasis et al., 2009 Genotype-imputation accuracy across worldwide human populations. Am. J. Hum. Genet. 84: 235-250.
12. Huang, L., M. Jakobsson, T. J. Pemberton, M. Ibrahim, T. Nyambo et al., 2011 Haplotype variation and genotype imputation in African populations. Genet. Epidemiol. 35: 766-780.
13. Hudson, R. R., 2002 Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics 18: 337-338.
14. Illumina, Inc. 2010 Genotyping rare variants. Technical Note: DNA Analysis, Pub. No. 370-2010-2008, San Diego, CA.
15. International HapMap Consortium, 2005 A haplotype map of the human genome. Nature 437: 1299-1320.
16. Jewett, E. M., M. Zawistowski, N. A. Rosenberg, and S. Zöllner, 2012 A coalescent model for genotype imputation. Genetics 194: 1239-1255.
17. Jostins, L., K. I. Morley, and J. C. Barrett, 2011 Imputation of lowfrequency variants using the HapMap3 benefits from large, diverse reference sets. Eur. J. Hum. Genet. 19: 662-666.
18. Kang, C. J., and P. Marjoram, 2012 A sample selection strategy for next-generation sequencing. Genet. Epidemiol. 36: 696-709.
19. Li, Y., C. Willer, S. Sanna, and G. Abecasis, 2009 Genotype imputation. Annu. Rev. Genomics Hum. Genet. 10: 387-406.
20. Li, Y., C. J. Willer, J. Ding, P. Scheet, and G. R. Abecasis, 2010 MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34: 816-834.
21. McKhann, H. I., C. Camilleri, A. Berard, T. Bataillon, J. L. David et al., 2004 Nested core collections maximizing genetic diversity in Arabidopsis thaliana. Plant J. 38: 193-202.
22. Nee, S., and R. M. May, 1997 Extinction and the loss of evolutionary history. Science 278: 692-694.
23. Nothnagel, M., D. Ellinghaus, S. Schreiber, M. Krawczak, and A. Franke, 2009 A comprehensive evaluation of SNP genotype imputation. Hum. Genet. 125: 163-171.
24. Pardi, F., and N. Goldman, 2005 Species choice for comparative genomics: being greedy works. PLoS Genet. 1: e71.
25. Pasaniuc, B., R. Avinery, T. Gur, C. F. Skibola, P. M. Bracci et al., 2010 A generic coalescent-based framework for the selection of a reference panel for imputation. Genet. Epidemiol. 34: 773-782.
26. Pei, Y. F., L. Zhang, J. Li, and H. W. Deng, 2010 Analyses and comparison of imputation-based association methods. PLoS ONE 5: e10827.
27. Reeves, P. A., L. W. Panella, and C. M. Richards, 2012 Retention of agronomically important variation in germplasm core collections: implications for allele mining. Theor. Appl. Genet. 124: 1155-1171.
28. Saitou, N., and M. Nei, 1987 The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425.
29. Scott, L. J., P. Muglia, X. Q. Kong, W. Guan, M. Flickinger et al., 2009 Genome-wide association and meta-analysis of bipolar disorder in individuals of European ancestry. Proc. Natl. Acad. Sci. USA 106: 7501-7506.
30. Steel, M., 2005 Phylogenetic diversity and the greedy algorithm. Syst. Biol. 54: 527-529.
31. The 1000 Genomes Project Consortium, 2010 A map of human genome variation from population-scale sequencing. Nature 467: 1061-1073.
32. Wang, J. R., F. P. de Villena, H. A. Lawson, J. M. Cheverud, G. A. Churchill et al., 2012 Imputation of single-nucleotide polymorphisms in inbred mice using local phylogeny. Genetics 190: 449-458.
33. Zawistowski, M., S. Gopalakrishnan, J. Ding, Y. Li, S. Grimm et al., 2010 Extending rare-variant testing strategies: analysis of noncoding sequence and imputed genotypes. Am. J. Hum. Genet. 87: 604-617.
34. Zeggini, E., L. J. Scott, R. Saxena, B. F. Voight, J. L. Marchini et al., 2008 Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat. Genet. 40: 638-645.