C. Schrooten

发表

Breeding value estimation for fat percentage using dense markers on Bos taurus autosome 14.

A. D. de Roos, C. Schrooten, E. Mullaart, 2007, Journal of dairy science.

Reliability of genomic evaluations in Holstein-Friesians using haplotypes based on the BovineHD BeadChip.

C. Schrooten, G. Schopen, 2013, Journal of dairy science.

Infrequent milk progesterone measurements in daughters enable bull selection for cow fertility.

R F Veerkamp, C. Schrooten, R. Veerkamp, 2004, Journal of dairy science.

Stochastic simulation of dairy cattle breeding schemes: Genetic evaluation of nucleus size and type

Chris Schrooten, C. Schrooten, J. A. Arendonk, 1992 .

Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds

C. Schrooten, M. Goddard, D. Boichard, 2020, Genetics Selection Evolution.

Improving Genomic Prediction of Crossbred and Purebred Dairy Cattle

Erica G. Jewell, C. Schrooten, M. Goddard, 2020, Frontiers in Genetics.

Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock

P. Visscher, C. Schrooten, R. Veerkamp, 2020, bioRxiv.

Efficient genomic prediction based on whole-genome sequence data using split-and-merge Bayesian variable selection

C. Schrooten, M. Calus, R. Veerkamp, 2016, Genetics Selection Evolution.

Including overseas performance information in genomic evaluations of Australian dairy cattle.

C. Schrooten, B. Hayes, J. Pryce, 2015, Journal of dairy science.

Breeding for a global dairy market using genomic selection

C. Schrooten, R. Veerkamp, J. A. Arendonk, 2009 .

Genomic prediction of breeding values using previously estimated SNP variances

C. Schrooten, M. Calus, R. Veerkamp, 2014, Genetics Selection Evolution.

Error rate for imputation from the Illumina BovineSNP50 chip to the Illumina BovineHD chip

C. Schrooten, M. Lund, V. Ducrocq, 2014, Genetics Selection Evolution.

Quantitative trait loci for milk production traits in dairy cattle

C. Schrooten, H. Bovenhuis, 2002 .

Multi-Country Genomic Selection

C. Schrooten, C. V. D. Linde, 2010 .

Genomic evaluation of a relatively small dairy cattle population by combination with a larger population.

C. Schrooten, J. Weller, H. Eding, 2015, Journal of dairy science.

Genomic prediction for numerically small breeds, using models with pre-selected and differentially weighted markers

C. Schrooten, R. Veerkamp, J. Houwing-Duistermaat, 2018, Genetics Selection Evolution.

Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds

C. Schrooten, M. Goddard, D. Boichard, 2020, Genetics Selection Evolution.

Utility of whole-genome sequence data for across-breed genomic prediction

C. Schrooten, R. Veerkamp, J. Houwing-Duistermaat, 2018, Genetics, selection, evolution : GSE.

Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein–Friesian cattle

C. Schrooten, M. Calus, R. Veerkamp, 2016, Genetics Selection Evolution.

Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations

C. Schrooten, M. Goddard, H. Daetwyler, 2021, Nature Communications.

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

I. M. MacLeod, B. J. Hayes, M. E. Goddard, 2016, BMC Genomics.

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

C. Schrooten, M. Goddard, B. Hayes, 2016, BMC Genomics.

Imputation of genotypes with low-density chips and its effect on reliability of direct genomic values in Dutch Holstein cattle.

C. Schrooten, M. Calus, H. Mulder, 2012, Journal of dairy science.

Genomic variation in dairy cattle - Identification and use

C. Schrooten, 2004 .

Detection of pleiotropic effects of quantitative trait loci in outbred populations using regression analysis.

C. Schrooten, H. Bovenhuis, 2002, Journal of dairy science.

Genetic progress in multistage dairy cattle breeding schemes using genetic markers.

C. Schrooten, H. Bovenhuis, J. V. van Arendonk, 2005, Journal of dairy science.

Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle.

C. Schrooten, W. Coppieters, H. Bovenhuis, 2000, Journal of dairy science.

Genome-wide association study to identify chromosomal regions associated with antibody response to Mycobacterium avium subspecies paratuberculosis in milk of Dutch Holstein-Friesians.

C. Schrooten, M. Nielen, J. V. van Arendonk, 2012, Journal of dairy science.

Genomic Prediction with 12.5 Million SNPs for 5503 Holstein Friesian Bulls

C. Schrooten, M. Calus, R. Veerkamp, 2014 .

Stochastic simulation of dairy cattle nucleus breeding schemes: Influence of breeding strategy and biased breeding values in the population.

C. Schrooten, J. A. Arendonk, C Schrooten, 1993, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Mapping QTL influencing gastrointestinal nematode burden in Dutch Holstein-Friesian dairy cattle

C. Schrooten, M. Georges, N. Tamma, 2009, BMC Genomics.

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

C. Schrooten, T. Druet, A. P. D. de Roos, 2010, Journal of dairy science.

A common reference population from four European Holstein populations increases reliability of genomic predictions

Guosheng Su, Tom Druet, Vincent Ducrocq, 2011, Genetics Selection Evolution.

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls.

C. Schrooten, R. Veerkamp, J. V. van Arendonk, 2011, Journal of dairy science.

Whole genome scan to detect chromosomal regions affecting multiple traits in dairy cattle.

C. Schrooten, M. Bink, H. Bovenhuis, 2004, Journal of dairy science.

Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle

C. Schrooten, M. Calus, R. Veerkamp, 2015, Genetics Selection Evolution.

Value of sharing cow reference population between countries on reliability of genomic prediction for milk yield traits.

C. Schrooten, H. Daetwyler, J. Pryce, 2019, Journal of dairy science.

Genomic Breeding Value Estimation in countries without large-scale genotyping: merging two training populations to increase genomic reliabilities.

C. Schrooten, M. Calus, J. Weller, 2018 .

Genomic selection at CRV

C. Schrooten, E. Mullaart, S. Beek, 2009 .

Efficient genomic prediction based on whole-genome sequence data using split-and-merge Bayesian variable selection

C. Schrooten, M. Calus, R. Veerkamp, 2016, Genetics Selection Evolution.

Comparing genomic prediction and GWAS with sequence information vs HD or 50k SNP chips

C. Schrooten, M. Calus, R. Veerkamp, 2015 .

Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.53 Genomic prediction across populations, using pre-selected markers and differential weight models

C. Schrooten, R. Veerkamp, J. Houwing-Duistermaat, 2018 .

Improving genomic prediction by EuroGenomics collaboration.

C. Schrooten, B. Guldbrandtsen, M. Lund, 2010 .

Genomic breeding value estimation using genetic markers, inferred ancestral haplotypes, and the genomic relationship matrix.

C. Schrooten, T. Druet, C Schrooten, 2011, Journal of dairy science.

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

C. Schrooten, M. Calus, R. Veerkamp, 2009, Genetics Selection Evolution.

Genomic prediction for numerically small breeds, using models with pre-selected and differentially weighted markers

C. Schrooten, R. Veerkamp, J. Houwing-Duistermaat, 2018, Genetics Selection Evolution.

Empirical and deterministic accuracies of across-population genomic prediction

C. Schrooten, M. Calus, R. Veerkamp, 2015, Genetics Selection Evolution.

A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

C. Schrooten, R. Veerkamp, A. Bouwman, 2020, Genetics Selection Evolution.

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls.

C. Schrooten, R. Veerkamp, J. V. Arendonk, 2011, Journal of dairy science.

GENETICS AND BREEDING Whole Genome Scan to Detect Quantitative Trait Loci for Conformation and Functional Traits in Dairy Cattle

C. Schrooten, W. Coppieters, H. Bovenhuis, 2000 .

A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

C. Schrooten, R. Veerkamp, A. Bouwman, 2020, Genetics Selection Evolution.

A common reference population from four European Holstein populations increases reliability of genomic predictions

C. Schrooten, B. Guldbrandtsen, M. Lund, 2011, Genetics Selection Evolution.