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Items: 1 to 20 of 194

1.

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
2.

High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep1.

O'Brien AC, Judge MM, Fair S, Berry DP.

J Anim Sci. 2019 Apr 3;97(4):1550-1567. doi: 10.1093/jas/skz043.

PMID:
30722011
3.

The feasibility of using low-density marker panels for genotype imputation and genomic prediction of crossbred dairy cattle of East Africa.

Aliloo H, Mrode R, Okeyo AM, Ni G, Goddard ME, Gibson JP.

J Dairy Sci. 2018 Oct;101(10):9108-9127. doi: 10.3168/jds.2018-14621. Epub 2018 Aug 1.

4.

Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes.

Berry DP, McParland S, Kearney JF, Sargolzaei M, Mullen MP.

Animal. 2014 Jun;8(6):895-903. doi: 10.1017/S1751731114000883.

PMID:
24840560
5.

Extent of linkage disequilibrium, consistency of gametic phase, and imputation accuracy within and across Canadian dairy breeds.

Larmer SG, Sargolzaei M, Schenkel FS.

J Dairy Sci. 2014 May;97(5):3128-41. doi: 10.3168/jds.2013-6826. Epub 2014 Feb 26.

6.

Within- and across-breed imputation of high-density genotypes in dairy and beef cattle from medium- and low-density genotypes.

Berry DP, McClure MC, Mullen MP.

J Anim Breed Genet. 2014 Jun;131(3):165-72. doi: 10.1111/jbg.12067. Epub 2013 Dec 5.

PMID:
24906026
7.

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.

8.

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.

9.

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.

10.

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.

11.

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.

12.

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.

13.

Accuracy of imputation of single nucleotide polymorphism marker genotypes from low-density panels in Japanese Black cattle.

Ogawa S, Matsuda H, Taniguchi Y, Watanabe T, Takasuga A, Sugimoto Y, Iwaisaki H.

Anim Sci J. 2016 Jan;87(1):3-12. doi: 10.1111/asj.12393. Epub 2015 May 28.

PMID:
26032028
14.

Evaluation of measures of correctness of genotype imputation in the context of genomic prediction: a review of livestock applications.

Calus MP, Bouwman AC, Hickey JM, Veerkamp RF, Mulder HA.

Animal. 2014 Nov;8(11):1743-53. doi: 10.1017/S1751731114001803. Epub 2014 Jul 21. Review.

PMID:
25045914
15.

Genotype imputation from various low-density SNP panels and its impact on accuracy of genomic breeding values in pigs.

Grossi DA, Brito LF, Jafarikia M, Schenkel FS, Feng Z.

Animal. 2018 Nov;12(11):2235-2245. doi: 10.1017/S175173111800085X. Epub 2018 Apr 30.

PMID:
29706144
16.

Genomic selection using low density marker panels with application to a sire line in pigs.

Wellmann R, Preuß S, Tholen E, Heinkel J, Wimmers K, Bennewitz J.

Genet Sel Evol. 2013 Jul 29;45:28. doi: 10.1186/1297-9686-45-28.

17.

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
18.

Strategies for genotype imputation in composite beef cattle.

Chud TC, Ventura RV, Schenkel FS, Carvalheiro R, Buzanskas ME, Rosa JO, Mudadu Mde A, da Silva MV, Mokry FB, Marcondes CR, Regitano LC, Munari DP.

BMC Genet. 2015 Aug 7;16:99. doi: 10.1186/s12863-015-0251-7.

19.

Ultra-low-density genotype panels for breed assignment of Angus and Hereford cattle.

Judge MM, Kelleher MM, Kearney JF, Sleator RD, Berry DP.

Animal. 2017 Jun;11(6):938-947. doi: 10.1017/S1751731116002457. Epub 2016 Nov 24.

PMID:
27881206
20.

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.

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