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Items: 1 to 20 of 198

1.

Imputation of high-density genotypes in the Fleckvieh cattle population.

Pausch H, Aigner B, Emmerling R, Edel C, Götz KU, Fries R.

Genet Sel Evol. 2013 Feb 13;45:3. doi: 10.1186/1297-9686-45-3.

2.

Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips.

Boison SA, Santos DJ, Utsunomiya AH, Carvalheiro R, Neves HH, O'Brien AM, Garcia JF, Sölkner J, da Silva MV.

J Dairy Sci. 2015 Jul;98(7):4969-89. doi: 10.3168/jds.2014-9213. Epub 2015 May 7.

3.

Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations.

Pryce JE, Johnston J, Hayes BJ, Sahana G, Weigel KA 2nd, McParland S, Spurlock D, Krattenmacher N, Spelman RJ, Wall E, Calus MP.

J Dairy Sci. 2014 Mar;97(3):1799-811. doi: 10.3168/jds.2013-7368. Epub 2014 Jan 25.

PMID:
24472132
4.

Accuracy of genotype imputation in Nelore cattle.

Carvalheiro R, Boison SA, Neves HH, Sargolzaei M, Schenkel FS, Utsunomiya YT, O'Brien AM, Sölkner J, McEwan JC, Van Tassell CP, Sonstegard TS, Garcia JF.

Genet Sel Evol. 2014 Oct 10;46:69. doi: 10.1186/s12711-014-0069-1.

5.

Strategies and utility of imputed SNP genotypes for genomic analysis in dairy cattle.

Khatkar MS, Moser G, Hayes BJ, Raadsma HW.

BMC Genomics. 2012 Oct 8;13:538. doi: 10.1186/1471-2164-13-538.

6.

Error rate for imputation from the Illumina BovineSNP50 chip to the Illumina BovineHD chip.

Schrooten C, Dassonneville R, Ducrocq V, Brøndum RF, Lund MS, Chen J, Liu Z, González-Recio O, Pena J, Druet T.

Genet Sel Evol. 2014 Feb 4;46:10. doi: 10.1186/1297-9686-46-10.

7.

Evaluation of the accuracy of imputed sequence variant genotypes and their utility for causal variant detection in cattle.

Pausch H, MacLeod IM, Fries R, Emmerling R, Bowman PJ, Daetwyler HD, Goddard ME.

Genet Sel Evol. 2017 Feb 21;49(1):24. doi: 10.1186/s12711-017-0301-x.

8.

Reliability of genomic prediction for German Holsteins using imputed genotypes from low-density chips.

Segelke D, Chen J, Liu Z, Reinhardt F, Thaller G, Reents R.

J Dairy Sci. 2012 Sep;95(9):5403-11. doi: 10.3168/jds.2012-5466.

PMID:
22916947
9.

Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle.

van Binsbergen R, Bink MC, Calus MP, van Eeuwijk FA, Hayes BJ, Hulsegge I, Veerkamp RF.

Genet Sel Evol. 2014 Jul 15;46:41. doi: 10.1186/1297-9686-46-41.

10.

Assets of imputation to ultra-high density for productive and functional traits.

Jiménez-Montero JA, Gianola D, Weigel K, Alenda R, González-Recio O.

J Dairy Sci. 2013 Sep;96(9):6047-58. doi: 10.3168/jds.2013-6793. Epub 2013 Jun 28.

PMID:
23810591
11.

Imputation of missing genotypes from low- to high-density SNP panel in different population designs.

He S, Wang S, Fu W, Ding X, Zhang Q.

Anim Genet. 2015 Feb;46(1):1-7. doi: 10.1111/age.12236. Epub 2014 Nov 28.

PMID:
25431355
12.

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
13.

Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle.

Brøndum RF, Guldbrandtsen B, Sahana G, Lund MS, Su G.

BMC Genomics. 2014 Aug 27;15:728. doi: 10.1186/1471-2164-15-728.

14.

Evaluation of developed low-density genotype panels for imputation to higher density in independent dairy and beef cattle populations.

Judge MM, Kearney JF, McClure MC, Sleator RD, Berry DP.

J Anim Sci. 2016 Mar;94(3):949-62. doi: 10.2527/jas.2015-0044.

PMID:
27065257
15.

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.

16.

Effect of reference population size and available ancestor genotypes on imputation of Mexican Holstein genotypes.

García-Ruiz A, Ruiz-Lopez FJ, Wiggans GR, Van Tassell CP, Montaldo HH.

J Dairy Sci. 2015 May;98(5):3478-84. doi: 10.3168/jds.2014-9132. Epub 2015 Mar 12.

PMID:
25771055
17.

High-density marker imputation accuracy in sixteen French cattle breeds.

Hozé C, Fouilloux MN, Venot E, Guillaume F, Dassonneville R, Fritz S, Ducrocq V, Phocas F, Boichard D, Croiseau P.

Genet Sel Evol. 2013 Sep 3;45:33. doi: 10.1186/1297-9686-45-33.

18.

Comparison of different imputation methods from low- to high-density panels using Chinese Holstein cattle.

Weng Z, Zhang Z, Zhang Q, Fu W, He S, Ding X.

Animal. 2013 May;7(5):729-35. doi: 10.1017/S1751731112002224. Epub 2012 Dec 11.

19.

Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle.

Ma P, Brøndum RF, Zhang Q, Lund MS, Su G.

J Dairy Sci. 2013 Jul;96(7):4666-77. doi: 10.3168/jds.2012-6316. Epub 2013 May 16.

20.

Effects of reduced panel, reference origin, and genetic relationship on imputation of genotypes in Hereford cattle.

Huang Y, Maltecca C, Cassady JP, Alexander LJ, Snelling WM, MacNeil MD.

J Anim Sci. 2012 Dec;90(12):4203-8. doi: 10.2527/jas.2011-4728. Epub 2012 Aug 2.

PMID:
22859753

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