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Items: 1 to 20 of 212

1.

A generic coalescent-based framework for the selection of a reference panel for imputation.

Paşaniuc B, Avinery R, Gur T, Skibola CF, Bracci PM, Halperin E.

Genet Epidemiol. 2010 Dec;34(8):773-82. doi: 10.1002/gepi.20505.

2.

Genotype-imputation accuracy across worldwide human populations.

Huang L, Li Y, Singleton AB, Hardy JA, Abecasis G, Rosenberg NA, Scheet P.

Am J Hum Genet. 2009 Feb;84(2):235-50. doi: 10.1016/j.ajhg.2009.01.013.

3.

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies.

Hao K, Chudin E, McElwee J, Schadt EE.

BMC Genet. 2009 Jun 16;10:27. doi: 10.1186/1471-2156-10-27.

4.

MaCH-admix: genotype imputation for admixed populations.

Liu EY, Li M, Wang W, Li Y.

Genet Epidemiol. 2013 Jan;37(1):25-37. doi: 10.1002/gepi.21690. Epub 2012 Oct 16.

5.

A genomewide admixture mapping panel for Hispanic/Latino populations.

Mao X, Bigham AW, Mei R, Gutierrez G, Weiss KM, Brutsaert TD, Leon-Velarde F, Moore LG, Vargas E, McKeigue PM, Shriver MD, Parra EJ.

Am J Hum Genet. 2007 Jun;80(6):1171-8. Epub 2007 Apr 20.

6.

Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.

Pasaniuc B, Zaitlen N, Lettre G, Chen GK, Tandon A, Kao WH, Ruczinski I, Fornage M, Siscovick DS, Zhu X, Larkin E, Lange LA, Cupples LA, Yang Q, Akylbekova EL, Musani SK, Divers J, Mychaleckyj J, Li M, Papanicolaou GJ, Millikan RC, Ambrosone CB, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante SJ, Bandera EV, Ingles SA, Press MF, Chanock SJ, Deming SL, Rodriguez-Gil JL, Palmer CD, Buxbaum S, Ekunwe L, Hirschhorn JN, Henderson BE, Myers S, Haiman CA, Reich D, Patterson N, Wilson JG, Price AL.

PLoS Genet. 2011 Apr;7(4):e1001371. doi: 10.1371/journal.pgen.1001371. Epub 2011 Apr 21.

7.

Haplotype variation and genotype imputation in African populations.

Huang L, Jakobsson M, Pemberton TJ, Ibrahim M, Nyambo T, Omar S, Pritchard JK, Tishkoff SA, Rosenberg NA.

Genet Epidemiol. 2011 Dec;35(8):766-80. doi: 10.1002/gepi.20626.

8.

Founder population-specific HapMap panel increases power in GWA studies through improved imputation accuracy and CNV tagging.

Surakka I, Kristiansson K, Anttila V, Inouye M, Barnes C, Moutsianas L, Salomaa V, Daly M, Palotie A, Peltonen L, Ripatti S.

Genome Res. 2010 Oct;20(10):1344-51. doi: 10.1101/gr.106534.110. Epub 2010 Sep 1.

9.

Similarity in recombination rate and linkage disequilibrium at CYP2C and CYP2D cytochrome P450 gene regions among Europeans indicates signs of selection and no advantage of using tagSNPs in population isolates.

Pimenoff VN, Laval G, Comas D, Palo JU, Gut I, Cann H, Excoffier L, Sajantila A.

Pharmacogenet Genomics. 2012 Dec;22(12):846-57. doi: 10.1097/FPC.0b013e32835a3a6d.

PMID:
23089684
10.

Imputation of low-frequency variants using the HapMap3 benefits from large, diverse reference sets.

Jostins L, Morley KI, Barrett JC.

Eur J Hum Genet. 2011 Jun;19(6):662-6. doi: 10.1038/ejhg.2011.10. Epub 2011 Mar 2.

11.

Improved ancestry inference using weights from external reference panels.

Chen CY, Pollack S, Hunter DJ, Hirschhorn JN, Kraft P, Price AL.

Bioinformatics. 2013 Jun 1;29(11):1399-406. doi: 10.1093/bioinformatics/btt144. Epub 2013 Mar 28.

12.

Enlarging a training set for genomic selection by imputation of un-genotyped animals in populations of varying genetic architecture.

Pimentel EC, Wensch-Dorendorf M, König S, Swalve HH.

Genet Sel Evol. 2013 Apr 26;45:12. doi: 10.1186/1297-9686-45-12.

13.

Ancestral components of admixed genomes in a Mexican cohort.

Johnson NA, Coram MA, Shriver MD, Romieu I, Barsh GS, London SJ, Tang H.

PLoS Genet. 2011 Dec;7(12):e1002410. doi: 10.1371/journal.pgen.1002410. Epub 2011 Dec 15.

14.

Assessment of genotype imputation performance using 1000 Genomes in African American studies.

Hancock DB, Levy JL, Gaddis NC, Bierut LJ, Saccone NL, Page GP, Johnson EO.

PLoS One. 2012;7(11):e50610. doi: 10.1371/journal.pone.0050610. Epub 2012 Nov 30.

15.

Comprehensive evaluation of imputation performance in African Americans.

Chanda P, Yuhki N, Li M, Bader JS, Hartz A, Boerwinkle E, Kao WH, Arking DE.

J Hum Genet. 2012 Jul;57(7):411-21. doi: 10.1038/jhg.2012.43. Epub 2012 May 31.

16.

Global similarity with local differences in linkage disequilibrium between the Dutch and HapMap-CEU populations.

Pardo L, Bochdanovits Z, de Geus E, Hottenga JJ, Sullivan P, Posthuma D, Penninx BW, Boomsma D, Heutink P.

Eur J Hum Genet. 2009 Jun;17(6):802-10. doi: 10.1038/ejhg.2008.248. Epub 2009 Jan 7.

17.

Long-range LD can confound genome scans in admixed populations.

Price AL, Weale ME, Patterson N, Myers SR, Need AC, Shianna KV, Ge D, Rotter JI, Torres E, Taylor KD, Goldstein DB, Reich D.

Am J Hum Genet. 2008 Jul;83(1):132-5; author reply 135-9. doi: 10.1016/j.ajhg.2008.06.005. No abstract available.

18.

Genotype imputation for African Americans using data from HapMap phase II versus 1000 genomes projects.

Sung YJ, Gu CC, Tiwari HK, Arnett DK, Broeckel U, Rao DC.

Genet Epidemiol. 2012 Jul;36(5):508-16. doi: 10.1002/gepi.21647. Epub 2012 May 29.

19.

Accuracy of genotype imputation in sheep breeds.

Hayes BJ, Bowman PJ, Daetwyler HD, Kijas JW, van der Werf JH.

Anim Genet. 2012 Feb;43(1):72-80. doi: 10.1111/j.1365-2052.2011.02208.x. Epub 2011 May 27.

PMID:
22221027
20.

Efficient genomewide selection of PCA-correlated tSNPs for genotype imputation.

Javed A, Drineas P, Mahoney MW, Paschou P.

Ann Hum Genet. 2011 Nov;75(6):707-22. doi: 10.1111/j.1469-1809.2011.00673.x. Epub 2011 Sep 8.

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