I. Aguilar, I. Misztal, D. L. Johnson, A. Legarra, S. Tsuruta et al., Hot topic : A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score, Journal of Dairy Science, vol.93, pp.743-752, 2010.
URL : https://hal.archives-ouvertes.fr/hal-02668766

I. Aguilar, I. Misztal, A. Legarra, and S. Tsuruta, Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation, Journal of Animal Breeding and Genetics, vol.128, pp.422-428, 2011.
URL : https://hal.archives-ouvertes.fr/hal-02645733

B. J. Bennett, C. R. Farber, L. Orozco, H. M. Kang, A. Ghazalpour et al., A highresolution association mapping panel for the dissection of complex traits in mice, Genome Research, vol.20, pp.281-290, 2010.

S. Bolormaa, J. E. Pryce, B. J. Hayes, and M. E. Goddard, Multivariate analysis of a genome-wide association study in dairy cattle, Journal of Dairy Science, vol.93, pp.3818-3833, 2010.

C. Y. Chen, I. Misztal, I. Aguilar, A. Legarra, and W. M. Muir, Effect of different genomic relationship matrices on accuracy and scale, Journal of Animal Science, vol.89, pp.2673-2679, 2011.
URL : https://hal.archives-ouvertes.fr/hal-02644418

O. F. Christensen and M. S. Lund, Genomic prediction when some animals are not genotyped, Genetics Selection Evolution, vol.42, 2010.

S. Forni, I. Aguilar, and I. Misztal, Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information, Genetics Selection Evolution, vol.43, 2011.

D. J. Garrick, J. F. Taylor, and R. L. Fernando, Deregressing estimated breeding values and weighting information for genomic regression analyses, Genetics Selection Evolution, vol.41, p.55, 2009.

D. Gianola, G. De-los-campos, W. G. Hill, E. Manfredi, and R. L. Fernando, Additive genetic variability and the Bayesian alphabet, Genetics, vol.183, pp.347-363, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02666251

M. E. Goddard and B. J. Hayes, Mapping genes for complex traits in domestic animals and their use in breeding programmes, Nature Reviews Genetics, vol.10, pp.381-391, 2009.

D. Habier, R. L. Fernando, K. Kizilkaya, and D. J. Garrick, Extension of the Bayesian alphabet for genomic selection, The 9th World Congress on Genetics Applied to Livestock Production, p.468, 2010.

C. R. Henderson, Sire evaluation and genetic trends, Journal of Animal Science, pp.10-41, 1973.

J. N. Hirschhorn and M. J. Daly, Genome-wide association studies for common diseases and complex traits, Nature Reviews Genetics, vol.6, pp.95-108, 2005.

E. K. Karlsson, I. Baranowska, C. M. Wade, N. H. Salmon-hillbertz, M. C. Zody et al., Efficient mapping of mendelian traits in dogs through genome-wide association, Nature Genetics, vol.39, pp.1321-1328, 2007.

A. Legarra, I. Aguilar, and I. Misztal, A relationship matrix including full pedigree and genomic information, Journal of Dairy Science, vol.92, pp.4656-4663, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02668784

A. Legarra and V. Ducrocq, Computational strategies for national integration of phenotypic, genomic and pedigree data in a single-step BLUP, Journal of Dairy Science

A. Legarra and I. Misztal, Technical note : Computing strategies in genome-wide selection, Journal of Dairy Science, vol.91, pp.360-366, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02658143

A. Legarra, C. Robert-granie, P. Croiseau, F. Guillaume, and S. Fritz, Improved Lasso for genomic selection, Genetics Research, vol.93, pp.77-87, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01000151

T. H. Meuwissen, B. J. Hayes, and M. E. Goddard, Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, pp.1819-1829, 2001.

K. Meyer and B. Tier, SNP Snappy'' : a strategy for fast genome-wide association studies fitting a full mixed model, Genetics, vol.190, pp.275-277, 2012.

I. Misztal, A. Legarra, and I. Aguilar, Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information, Journal of Dairy Science, vol.92, pp.4648-4655, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02668727

I. Misztal, S. Tsuruta, T. Strabel, B. Auvray, T. Druet et al., BLUPF90 and related programs (BGF90), The 7th World Congress Genetics Application Livestock Production, p.28, 2002.

R. Mrode, M. P. Coffey, I. Strade´n, T. H. Meuwissen, J. B. Kaam et al., A comparison of various methods for the computation of genomic breeding values of dairy cattle using software at genomicselection.net, the 9th World Congress on Genetics Applied to Livestock Production, 2010.

N. Orr, W. Back, J. Gu, P. Leegwater, P. Govindarajan et al., , 2010.

, Genome-wide SNP association-based localization of a dwarfism gene in Friesian dwarf horses, Animal Genetics, vol.41, pp.2-7

T. Ostersen, O. F. Christensen, M. Henryon, B. Nielsen, G. Su et al., Degressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs, Genetics Selection Evolution, vol.43, issue.1, p.38, 2011.

J. E. Pryce, S. Bolormaa, A. J. Chamberlain, P. J. Bowman, K. Savin et al., A validated genome-wide association study in 2 dairy cattle breeds for milk production and fertility traits using variable length haplotypes, Journal of Dairy Science, vol.93, pp.3331-3345, 2010.

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

B. Servin and M. Stephens, Imputation-based analysis of association studies : candidate regions and quantitative traits, PLoS Genetics, vol.3, p.114, 2007.
URL : https://hal.archives-ouvertes.fr/hal-02662573

M. J. Sillanpaa, Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses, Heredity, vol.106, pp.511-519, 2011.

I. Stranden and D. J. Garrick, Technical note : Derivation of equivalent computing algorithms for genomic predictions and reliabilities of animal merit, Journal of Dairy Science, vol.92, pp.2971-2975, 2009.

X. Sun, R. L. Fernando, D. J. Garrick, and J. C. Dekkers, An iterative approach for efficient calculation of breeding values and genome-wide association analysis using weighted genomic BLUP, Journal of Animal Science, vol.89, p.11, 2011.

P. M. Vanraden, C. P. Van-tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel et al., Invited review : Reliability of genomic predictions for North American Holstein bulls, Journal of Dairy Science, vol.92, pp.16-24, 2009.

T. M. Villumsen, L. Janss, and M. S. Lund, The importance of haplotype length and heritability using genomic selection in dairy cattle, Journal of Animal Breeding and Genetics, vol.126, pp.3-13, 2009.

P. M. Visscher, S. Macgregor, B. Benyamin, G. Zhu, S. Gordon et al., Genome partitioning of genetic variation for height from 11,214 sibling pairs, American Journal of Human Genetics, vol.81, pp.1104-1110, 2007.

Z. G. Vitezica, I. Aguilar, I. Misztal, and A. Legarra, Bias in genomic predictions for populations under selection, Genetics Research, vol.93, pp.357-366, 2011.
URL : https://hal.archives-ouvertes.fr/hal-02647567

J. Wakefield, Bayes factors for genome-wide association studies : comparison with P-values, Genetic Epidemiology, vol.33, pp.79-86, 2009.

S. Xu, An expectation-maximization algorithm for the Lasso estimation of quantitative trait locus effects, Heredity, vol.105, pp.483-494, 2010.

Z. Zhang, J. Liu, X. Ding, P. Bijma, D. J. De-koning et al., Best linear unbiased prediction of genomic breeding values using a trait-specific markerderived relationship matrix, PLoS One, vol.5, 2010.

K. T. Zondervan and L. R. Cardon, The complex interplay among factors that influence allelic association, Nature Reviews Genetics, vol.5, pp.89-100, 2004.