A fast indirect method to compute functions of genomic relationships concerning genotyped and ungenotyped individuals, for diversity management

[1]  K. Meyer,et al.  Estimates of genetic trend for single-step genomic evaluations , 2018, Genetics Selection Evolution.

[2]  I. Strandén,et al.  Solving efficiently large single‐step genomic best linear unbiased prediction models , 2017, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[3]  O. F. Christensen,et al.  Metafounders are related to Fst fixation indices and reduce bias in single-step genomic evaluations , 2017, Genetics Selection Evolution.

[4]  I Misztal,et al.  Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. , 2016, Journal of dairy science.

[5]  Ignacy Misztal,et al.  Inexpensive Computation of the Inverse of the Genomic Relationship Matrix in Populations with Small Effective Population Size , 2015, Genetics.

[6]  Ignacy Misztal,et al.  Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships , 2015, Genetics.

[7]  J. Woolliams,et al.  Genetic contributions and their optimization. , 2015, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[8]  Ignacy Misztal,et al.  Single Step, a general approach for genomic selection , 2014 .

[9]  M. Suzuki,et al.  Application of supernodal sparse factorization and inversion to the estimation of (co)variance components by residual maximum likelihood. , 2014, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[10]  A. Legarra,et al.  Within- and across-breed genomic predictions and genomic relationships for Western Pyrenees dairy sheep breeds Latxa, Manech, and Basco-Béarnaise. , 2014, Journal of dairy science.

[11]  C. Robert-Granié,et al.  A first step toward genomic selection in the multi-breed French dairy goat population. , 2013, Journal of dairy science.

[12]  O. F. Christensen,et al.  Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation , 2012, Genetics Selection Evolution.

[13]  P Madsen,et al.  Single-step methods for genomic evaluation in pigs. , 2012, Animal : an international journal of animal bioscience.

[14]  J. Woolliams,et al.  Genomic selection requires genomic control of inbreeding , 2012, Genetics Selection Evolution.

[15]  I Misztal,et al.  Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation. , 2011, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[16]  I Misztal,et al.  Bias in genomic predictions for populations under selection. , 2011, Genetics research.

[17]  Andrés Legarra,et al.  A note on the rationale for estimating genealogical coancestry from molecular markers , 2011, Genetics Selection Evolution.

[18]  Pierre Martin,et al.  Optimized diffusion of buck semen for saving genetic variability in selected dairy goat populations , 2011, BMC Genetics.

[19]  B S Weir,et al.  Variation in actual relationship as a consequence of Mendelian sampling and linkage. , 2011, Genetics research.

[20]  P. Visscher,et al.  Reconciling the analysis of IBD and IBS in complex trait studies , 2010, Nature Reviews Genetics.

[21]  I Misztal,et al.  Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. , 2010, Journal of dairy science.

[22]  M. Lund,et al.  Genomic prediction when some animals are not genotyped , 2010, Genetics Selection Evolution.

[23]  I Misztal,et al.  A relationship matrix including full pedigree and genomic information. , 2009, Journal of dairy science.

[24]  J. Colleau,et al.  A mating method accounting for inbreeding and multi-trait selection in dairy cattle populations , 2009, Genetics Selection Evolution.

[25]  P. VanRaden,et al.  Efficient methods to compute genomic predictions. , 2008, Journal of dairy science.

[26]  Jean-Jacques Colleau,et al.  An indirect approach to the extensive calculation of relationship coefficients , 2002, Genetics Selection Evolution.

[27]  M. Goddard,et al.  Prediction of total genetic value using genome-wide dense marker maps. , 2001, Genetics.

[28]  T. Meuwissen Maximizing the response of selection with a predefined rate of inbreeding. , 1997, Journal of animal science.

[29]  Ed Anderson,et al.  LAPACK Users' Guide , 1995 .

[30]  Ed Anderson,et al.  LAPACK users' guide - [release 1.0] , 1992 .

[31]  R. L. Quaas,et al.  Computing the Diagonal Elements and Inverse of a Large Numerator Relationship Matrix , 1976 .

[32]  C. R. Henderson A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values , 1976 .

[33]  John Maynard Smith,et al.  The hitch-hiking effect of a favourable gene. , 1974, Genetical research.

[34]  C. E. Terrill,et al.  Systematic procedures for calculating inbreeding coefficients. , 1949, The Journal of heredity.

[35]  S. Wright,et al.  Isolation by Distance. , 1943, Genetics.

[36]  Ignacy Misztal,et al.  Efficient computations of genomic relationship matrix and other matrices used in the single-step evaluation , 2010 .

[37]  Ignacy Misztal,et al.  FSPAK: an interface for public domain sparse matrix subroutines , 1994 .

[38]  J. M. Smith,et al.  The hitch-hiking effect of a favourable gene. , 1974, Genetical research.