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Results: 1 to 20 of 141

Similar articles for PubMed (Select 24663187)

1.

Impact of reference population on accuracy of imputation from 6K to 50K single nucleotide polymorphism chips in purebred and crossbreed beef cattle.

Ventura RV, Lu D, Schenkel FS, Wang Z, Li C, Miller SP.

J Anim Sci. 2014 Apr;92(4):1433-44. doi: 10.2527/jas.2013-6638. Epub 2014 Mar 18.

2.

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.

PMID:
24582440
3.

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.

4.

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.

5.

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.

6.

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
7.

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.

8.

Accuracy of genome-wide imputation in Braford and Hereford beef cattle.

Piccoli ML, Braccini J, Cardoso FF, Sargolzaei M, Larmer SG, Schenkel FS.

BMC Genet. 2014 Dec 29;15:157. doi: 10.1186/s12863-014-0157-9.

9.

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
10.

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.

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.

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.

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.

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
15.

Imputation of genotypes in Danish purebred and two-way crossbred pigs using low-density panels.

Xiang T, Ma P, Ostersen T, Legarra A, Christensen OF.

Genet Sel Evol. 2015 Jun 30;47:54. doi: 10.1186/s12711-015-0134-4.

16.

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
17.

An ensemble-based approach to imputation of moderate-density genotypes for genomic selection with application to Angus cattle.

Sun C, Wu XL, Weigel KA, Rosa GJ, Bauck S, Woodward BW, Schnabel RD, Taylor JF, Gianola D.

Genet Res (Camb). 2012 Jun;94(3):133-50. doi: 10.1017/S001667231200033X. Epub 2012 Jul 18.

PMID:
22809677
18.

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
19.

Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle.

Druet T, Schrooten C, de Roos AP.

J Dairy Sci. 2010 Nov;93(11):5443-54. doi: 10.3168/jds.2010-3255.

PMID:
20965360
20.

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.

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