اثر تراکم نشانگرها و اندازه جمعیت مرجع بر صحت مستندسازی در داده شبیه سازی شده

Browning S. and Browning B. 2011. Haplotype phasing: Ex­isting methods and new developments. Nature Reviews Genetics, 12: 703-714.

Browning B., Zhou Y. and Browning S. 2018. A one-penny imputed genome from next-generation reference panels. The American Journal of Human Genetics, 103: 338-348.

Carvalheiro R., Boison S., Neves H., Sargolzaei M., Schenkel F., Utsunomiya Y., O’Brien A., Solkner J., McEwan J., Van Tassell C., Sonstegard T. and Garcia J. 2014. Accuracy of genotype imputation in Nelore cattle. Genetics Selection Evolution, 46, 69.

Daetwyler H., Wiggans G., Hayes B., Woolliams J. and Goddard M. 2011. Imputation of missing genotypes from sparse to high density using long-range phasing. Genetics, 189: 317-327.

Elsen J. M. 2016. Approximated prediction of genomic selection accuracy when reference and candidate populations are related. Genetics Selection Evolution, 48, 16.

Ghoreishifar S. M., Moradi- Shahrbabak H., Moradi- Shahrb­abak M., Nicolazzi E. L., Williams J. L., Iamartino D. and Nejati- Javaremi A. 2018. Accuracy of imputation of single-nucleotide polymorphism marker genotypes for water buffaloes (Bubalus bubalis) using different refer­ence population sizes and imputation tools. Livestock Science, 216: 174-182.

Hayes B., Bowman P., Chamberlain A. and Goddard M. 2009. Invited review: Genomic selection in dairy cattle. Journal of Dairy Science, 92: 433-443.

Hickey J., Kinghorn B., Tier B., Wilson J., Dunstan N. and Van der Werf J. 2011. A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes. Genetics Selection Evolution, 43, 12.

Hong L. S, Clark S. and Van der Werf J. 2017. Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship. Plos One, 21, 1-22.

Kranjčevičová A., Kašná E., Brzáková M. A, Přiby J. and Vostrý L. 2019. Impact of reference population size and marker density on accuracy of population imputation, Czech Journal of Animal Science, 64: 405-410.

Mulder H., Calus M., Druet T. and Schrooten C. 2012. Impu­tation of genotypes with low-density chips and its effect on reliability of direct genomic values in Dutch Holstein cattle. Journal of Dairy Science, 95: 876-889.

Nicolazzi E., Biffani S. and Jansen G. 2013. Short communica­tion: Imputing genotypes using PedImpute fast algorithm combining pedigree and population information. Journal of Dairy Science, 96: 2649-2653.

Olson K. M., VanRaden P. M., Tooker M. E. and Cooper T. A. 2011. Differences among methods to validate genomic evaluations for dairy cattle. Journal of Dairy Science, 94: 2613-2620.

Sargolzaei M., Chesnais J. and Schenkel F. 2014. A new ap­proach for efficient genotype imputation using informa­tion from relatives. BMC Genomics, 15, 12.

Sargolzaei M. and Schenkel F. S. 2009. QMSim: a large-scale genome simulator for livestock. Bioinformatics, 25: 680-681.

Schaeffer L. 2006. Strategy for applying genome-wide selection in dairy cattle. Journal of Animal Breeding and Genetics, 23: 218-223.

Schurz H., Stephanie J. M., van Helden P. D., Tromp G., Hoal E. G., Kinnear C. J.  and Möller M. 2019. Evaluating the accuracy of imputation methods in a five-way admixed population. Frontiers in Genetics, 10: 34.

VanRaden P., O’Connell J., Wiggans G. and Weigel K. 2011. Genomic evaluations with many more genotypes. Genet­ics Selection Evolution, 43, 1-10.

VanRaden P., Sun C. and O’Connell J. 2015. Fast imputation using medium or low-coverage sequence data. BMC Genetics, 16(82): 2039-2042.

Ventura R., Lu D., Schenkel F. S., Wang Z., Li C. and Miller S. P. 2014. Impact of reference population on accuracy of im­putation from 6K to 50K single nucleotide polymorphism chips in purebred and crossbreed beef cattle. Journal of Animal Science, 92: 1433-1444.

Wang Y., Lin G., Li C. and Stothard P. 2016. Genotype imputa­tion methods and their effects on genomic predictions in cattle. Springer Science Reviews, 4: 79-98.

Whalen A., Gorjanc G., Ros- Freixedes R. and Hickey J. 2018. Assessment of the performance of hidden Markov models for imputation in animal breeding. Genetics Selection Evolution, 50, 4-10.

Zhang Z. and Druet T. 2010. Marker imputation with low-density marker panels in Dutch Holstein cattle. Journal of Dairy Science, 93: 5487-5494.