GVCBLUP: A computer package for genomic prediction and variance component estimation of additive and dominance effects

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Wang, Chunkao ^a   Prakapenka, Dzianis ^b   Wang, Shengwen ^a   Pulugurta, Sujata ^a   Runesha, Hakizumwami B ^b   Da, Yang ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

Author keywords

BLUP; Genomic selection; GVCBLUP; Heritability; Variance component

Indexed keywords

BLUP; GENOMIC SELECTION; GVCBLUP; HERITABILITY; VARIANCE COMPONENTS;

ALGORITHM; ANIMAL; ARTICLE; BREEDING; COMPUTER PROGRAM; GENETIC MARKER; GENETICS; GENOMICS; GENOTYPE; METHODOLOGY; PHENOTYPE; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; ANIMALS; BREEDING; GENETIC MARKERS; GENOMICS; GENOTYPE; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; SOFTWARE;

EID: 84906766480     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-270     Document Type: Article

References (23)

1. Meuwissen THE, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001, 157(4):1819-1829. 1461589, 11290733.
2. VanRaden P. Efficient methods to compute genomic predictions. J Dairy Sci 2008, 91(11):4414-4423. 10.3168/jds.2007-0980, 18946147.
3. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW. Common SNPs explain a large proportion of the heritability for human height. Nat Genet 2010, 42(7):565-569. 10.1038/ng.608, 3232052, 20562875.
4. Falconer DS, Mackay TFC. Introduction to Quantitative Genetics 1996, Harlow, Essex, UK: Longmans Green, 4.
5. Da Y, Wang C, Wang S, Hu G. Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers. PLoS One 2014, 9(1):e87666. 10.1371/journal.pone.0087666, 3907568, 24498162.
6. Hu G, Wang C, Da Y. Genomic heritability estimation for the early life-history transition related to propensity to migrate in wild rainbow and steelhead trout populations. Ecol Evol 2014, doi:101002/ece31038.
7. Vitezica ZG, Varona L, Legarra A. On the additive and dominant variance and covariance of individuals within the genomic selection scope. Genetics 2013, 195(4):1223-1230. 10.1534/genetics.113.155176, 24121775.
8. Nishio M, Satoh M. Including dominance effects in the genomic BLUP method for genomic evaluation. PLoS One 2014, 9(1):e85792. 10.1371/journal.pone.0085792, 3885721, 24416447.
9. Sun C, VanRaden P, O'Connell J, Weigel K, Gianola D. Mating programs including genomic relationships and dominance effects. J Dairy Sci 2013, 96(12):8014-8023. 10.3168/jds.2013-6969, 24119810.
10. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011, 88(1):76-82. 10.1016/j.ajhg.2010.11.011, 3014363, 21167468.
11. Pe´rez P, de Los CG, Crossa J, Gianola D. Genomic-enabled prediction based on molecular markers and pedigree using the Bayesian linear regression package in R. Plant Genome 2010, 3(2):106-116. 10.3835/plantgenome2010.04.0005, 3091623, 21566722.
12. Fernando R, Garrick D. GenSel-User Manual for a Portfolio of Genomic Selection Related Analyses 2008, Ames: Animal Breeding and Genetics, Iowa State University, [http://taurus.ansci.iastate.edu/].
13. Su G, Christensen OF, Ostersen T, Henryon M, Lund MS. Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. PLoS One 2012, 7(9):e45293. 10.1371/journal.pone.0045293, 3441703, 23028912.
14. Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, Lawlor TJ. Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J Dairy Sci 2010, 93(2):743-752. 10.3168/jds.2009-2730, 20105546.
15. Da Y, Wang S. Joint genomic prediction and estimation of variance components of additive and dominance effects using SNP markers. Abstract P1004. Plant and Animal Genome XXI, January 12-16, 2013. San Diego. [https://pag.confex.com/pag/xxi/webprogram/Paper7396.html].
16. Eigen V3. [http://eigen.tuxfamily.org].
17. Intel Math Kernel Library Reference Manual. Doc. No. 630813-061US, MKL 11.0, update 5. [http://download-software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mklman/mklman.pdf].
18. Wang S, Dvorkin D, Da Y. SNPEVG: a graphical tool for GWAS graphing with mouse clicks. BMC Bioinformatics 2012, 13(1):319. 10.1186/1471-2105-13-319, 3527193, 23199373.
19. Cleveland MA, Hickey JM, Forni S. A common dataset for genomic analysis of livestock populations. G3: Genes| Genomes|Genetics 2012, 2(4):429-435.
20. Ma L, Runesha HB, Dvorkin D, Garbe J, Da Y. Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies. BMC Bioinformatics 2008, 9(1):315. 10.1186/1471-2105-9-315, 2503991, 18644146.
21. Ma L, Wiggans G, Wang S, Sonstegard T, Yang J, Crooker B, Cole J, Van Tassell C, Lawlor T, Da Y. Effect of sample stratification on dairy GWAS results. BMC Genomics 2012, 13(1):536. 10.1186/1471-2164-13-536, 3496570, 23039970.
22. Hu G, Wang C, Da Y. Genomic heritability estimation for the early life-history transition related to propensity to migrate in wild rainbow and steelhead trout populations. Ecology Evol 2014, 4(8):1381-1388.
23. Wang C, Prakapenka D, Wang S, Runesha HB, Da Y. GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects using SNP markers. Version 3.3. Department of Animal Science, University of Minnesota 2013,