Imputation of high-density genotypes in the Fleckvieh cattle population

[1]  L. Alexander,et al.  Effects of reduced panel, reference origin, and genetic relationship on imputation of genotypes in Hereford cattle. , 2012, Journal of animal science.

[2]  P. Ma,et al.  Short communication: genotype imputation within and across Nordic cattle breeds. , 2012, Journal of dairy science.

[3]  P. Ma,et al.  Comparison of genomic predictions using medium-density (∼54,000) and high-density (∼777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle populations. , 2012, Journal of dairy science.

[4]  J. Marchini,et al.  Fast and accurate genotype imputation in genome-wide association studies through pre-phasing , 2012, Nature Genetics.

[5]  M Erbe,et al.  Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. , 2012, Journal of dairy science.

[6]  B. Kinghorn,et al.  A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation , 2012, Genetics Selection Evolution.

[7]  J. Woolliams,et al.  The identification of SNPs with indeterminate positions using the Equine SNP50 BeadChip. , 2012, Animal Genetics.

[8]  Chuanyu Sun,et al.  An ensemble-based approach to imputation of moderate-density genotypes for genomic selection with application to Angus cattle. , 2012, Genetics research.

[9]  Xiaolong Wang,et al.  Identification of QTL for UV-Protective Eye Area Pigmentation in Cattle by Progeny Phenotyping and Genome-Wide Association Analysis , 2012, PloS one.

[10]  B. Hayes,et al.  Accuracy of genomic predictions of residual feed intake and 250-day body weight in growing heifers using 625,000 single nucleotide polymorphism markers. , 2012, Journal of dairy science.

[11]  José Crossa,et al.  Factors Affecting the Accuracy of Genotype Imputation in Populations from Several Maize Breeding Programs , 2012 .

[12]  João Fadista,et al.  Genomic Position Mapping Discrepancies of Commercial SNP Chips , 2012, PloS one.

[13]  M. Lyons,et al.  Low-Pass Genome-Wide Sequencing and Variant Inference Using Identity-by-Descent in an Isolated Human Population , 2012, Genetics.

[14]  J. Kijas,et al.  Accuracy of genotype imputation in sheep breeds. , 2012, Animal genetics.

[15]  C. Schrooten,et al.  Imputation of genotypes with low-density chips and its effect on reliability of direct genomic values in Dutch Holstein cattle. , 2012, Journal of dairy science.

[16]  O. Delaneau,et al.  A linear complexity phasing method for thousands of genomes , 2011, Nature Methods.

[17]  Alison L. Van Eenennaam,et al.  Hot topic: performance of bovine high-density genotyping platforms in Holsteins and Jerseys. , 2011, Journal of dairy science.

[18]  J. Marchini,et al.  Genotype Imputation with Thousands of Genomes , 2011, G3: Genes | Genomes | Genetics.

[19]  F. Schenkel,et al.  Rates of inbreeding and genetic diversity in Canadian Holstein and Jersey cattle. , 2011, Journal of dairy science.

[20]  B. Browning,et al.  Haplotype phasing: existing methods and new developments , 2011, Nature Reviews Genetics.

[21]  G. Thaller,et al.  Pedigree analysis and inbreeding effects on calving traits in large dairy herds in Germany. , 2011, Journal of dairy science.

[22]  John A Woolliams,et al.  Imputation of Missing Genotypes From Sparse to High Density Using Long-Range Phasing , 2011, Genetics.

[23]  M P L Calus,et al.  Imputation of missing single nucleotide polymorphism genotypes using a multivariate mixed model framework. , 2011, Journal of animal science.

[24]  V Ducrocq,et al.  Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations. , 2011, Journal of dairy science.

[25]  Bruce Tier,et al.  A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes , 2011, Genetics Selection Evolution.

[26]  P. VanRaden,et al.  Genomic evaluations with many more genotypes , 2011, Genetics Selection Evolution.

[27]  G. Abecasis,et al.  MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes , 2010, Genetic epidemiology.

[28]  T. Druet,et al.  Marker imputation with low-density marker panels in Dutch Holstein cattle. , 2010, Journal of dairy science.

[29]  C. Schrooten,et al.  Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle. , 2010, Journal of dairy science.

[30]  Flavio S Schenkel,et al.  Characteristics of linkage disequilibrium in North American Holsteins , 2010, BMC Genomics.

[31]  M. Goddard,et al.  Accurate Prediction of Genetic Values for Complex Traits by Whole-Genome Resequencing , 2010, Genetics.

[32]  Tom Druet,et al.  A Hidden Markov Model Combining Linkage and Linkage Disequilibrium Information for Haplotype Reconstruction and Quantitative Trait Locus Fine Mapping , 2010, Genetics.

[33]  P. Lichtner,et al.  The impact of genetic relationship information on genomic breeding values in German Holstein cattle , 2010, Genetics Selection Evolution.

[34]  P. Lichtner,et al.  The pattern of linkage disequilibrium in German Holstein cattle. , 2009, Animal genetics.

[35]  P. Donnelly,et al.  Designing Genome-Wide Association Studies: Sample Size, Power, Imputation, and the Choice of Genotyping Chip , 2009, PLoS genetics.

[36]  David R. Kelley,et al.  A whole-genome assembly of the domestic cow, Bos taurus , 2009, Genome Biology.

[37]  Robert D Schnabel,et al.  Genome-Wide Survey of SNP Variation Uncovers the Genetic Structure of Cattle Breeds , 2009, Science.

[38]  Gonçalo Abecasis,et al.  Genotype-imputation accuracy across worldwide human populations. , 2009, American journal of human genetics.

[39]  B. Browning,et al.  A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. , 2009, American journal of human genetics.

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

[41]  Hong-Wen Deng,et al.  Analyses and Comparison of Accuracy of Different Genotype Imputation Methods , 2008, PloS one.

[42]  Sharon R. Browning,et al.  Missing data imputation and haplotype phase inference for genome-wide association studies , 2008, Human Genetics.

[43]  F. Schenkel,et al.  Extent of linkage disequilibrium in Holstein cattle in North America. , 2008, Journal of dairy science.

[44]  W. Barris,et al.  Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel , 2008, BMC Genomics.

[45]  John B. Cole,et al.  Application note: PyPedal: A computer program for pedigree analysis , 2007 .

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

[47]  G. Kistemaker,et al.  Comparison of different imputation methods , 2011 .

[48]  D. Boichard,et al.  Imputation Efficiency with Different Low Density Chips in French Dairy and Beef Breeds , 2011 .

[49]  G. Abecasis,et al.  Genotype imputation. , 2009, Annual review of genomics and human genetics.

[50]  M. Goddard,et al.  Genomic selection based on dense genotypes inferred from sparse genotypes. , 2009 .

[51]  John B. Cole,et al.  PyPedal: A computer program for pedigree analysis , 2007 .

[52]  G. Abecasis,et al.  Merlin—rapid analysis of dense genetic maps using sparse gene flow trees , 2002, Nature Genetics.