Additional file 4: Figure S4. Heritabilities of QTL (h2 QTL) according to number of QTL markers for fat and protein yield. HOLDK = Danish Holstein, HOLFR = French Holstein, JER = Jersey and RDC = Danish Red. Reliabilities are shown for within-breed prediction using 50 K and QTL components containing a restricted number of markers in a QTL interval with a p value below a threshold of 10−10 (closed circles), 10−14 (open circles) or 10−20 (triangles) in a multi breed GWAS
Background: Genome wide association studies (GWAS) in most cattle breeds result in large genomic int...
BACKGROUND: Although simulation studies show that combining multiple breeds in one reference populat...
Additional file 1: Table S1. Number of rare and low-frequency variants (RLFV) selected for inclusion...
Additional file 5: Table S1. Posterior standard deviations of genomic correlations between breeds. A...
Additional file 1: Figure S1. Reliabilities of genomic predictions in different scenarios for fat an...
International audienceAbstractBackgroundSequence data can potentially increase the reliability of ge...
Additional file 4: Table S4. Description of other significant QTL regions detected in within-breed (...
Additional file 3: Table S3. Reliabilities of genomic prediction using various marker sets for the i...
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregat...
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregat...
Additional file 5: Table S5. Functional annotations of variants included within confidence intervals...
Additional file 2: Table S2. Number of variants included within confidence intervals for each QTL re...
Additional file 9: Figure S4. Relationship between bias of genomic predictions and changes in predic...
Additional file 4: Table S4. Bias of the GEBV measured by regression slope using various marker sets...
Additional file 6: Table S6. The additive genetic variances explained in the models for one replicat...
Background: Genome wide association studies (GWAS) in most cattle breeds result in large genomic int...
BACKGROUND: Although simulation studies show that combining multiple breeds in one reference populat...
Additional file 1: Table S1. Number of rare and low-frequency variants (RLFV) selected for inclusion...
Additional file 5: Table S1. Posterior standard deviations of genomic correlations between breeds. A...
Additional file 1: Figure S1. Reliabilities of genomic predictions in different scenarios for fat an...
International audienceAbstractBackgroundSequence data can potentially increase the reliability of ge...
Additional file 4: Table S4. Description of other significant QTL regions detected in within-breed (...
Additional file 3: Table S3. Reliabilities of genomic prediction using various marker sets for the i...
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregat...
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregat...
Additional file 5: Table S5. Functional annotations of variants included within confidence intervals...
Additional file 2: Table S2. Number of variants included within confidence intervals for each QTL re...
Additional file 9: Figure S4. Relationship between bias of genomic predictions and changes in predic...
Additional file 4: Table S4. Bias of the GEBV measured by regression slope using various marker sets...
Additional file 6: Table S6. The additive genetic variances explained in the models for one replicat...
Background: Genome wide association studies (GWAS) in most cattle breeds result in large genomic int...
BACKGROUND: Although simulation studies show that combining multiple breeds in one reference populat...
Additional file 1: Table S1. Number of rare and low-frequency variants (RLFV) selected for inclusion...