1,720,983 research outputs found
Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle
No full textAbstract Background In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny. Methods To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered. Results Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high. Conclusions The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.</p
Evidence of biases in genetic evaluations due to genomic preselection in dairy cattle
No full textA genomic preselection step of young sires is now often included in dairy cattle breeding schemes. Young sires are selected based on their genomic breeding values. They have better Mendelian sampling contribution so that the assumption of random Mendelian sampling term in genetic evaluations is clearly violated. When these sires and their progeny are evaluated using BLUP, it is feared that estimated breeding values are biased. The effect of genomic selection on genetic evaluations was studied through simulations keeping the structure of the Holstein population in France. The quality of genetic evaluations was assessed by computing bias and accuracy from the difference and correlation between true and estimated breeding values, respectively, and also the mean square error of prediction. Different levels of heritability, selection intensity, and accuracy of genomic evaluation were tested. After only one generation and whatever the scenario, breeding values of preselected young sires and their daughters were significantly underestimated and their accuracy was decreased. Genomic preselection needs to be accounted for in genetic evaluation models
Effect of a national genomic preselection on the international genetic evaluations
No full textGenomic preselection of young bulls is now widely implemented in dairy breeding schemes, especially in the Holstein breed. However, if this step is not accounted for in genetic evaluation models, the national breeding values of bulls retained by a genomic preselection and of their progeny are estimated with bias. It follows that countries participating in international genetic evaluations will provide a selected and possibly biased set of data to the Interbull Centre (Swedish University of Agricultural Sciences, Uppsala, Sweden). The objective of the study was to show evidence of bias at the international level due to a genomic preselection step in national breeding schemes. The consequence of a genomic preselection for the international evaluations (i.e., using selected and biased national estimated breeding values) was simulated using actual national estimated breeding values as a proxy for genomically enhanced breeding values. Data were provided for 3 countries with a large population of Holstein bulls. International breeding values from simulated scenarios were compared with international breeding values using all available data, assumed to be complete and unbiased. Bias was measured among young bulls retained by a genomic preselection and their contemporaries in other countries. The results were analyzed by traits measured within each country and by country of origin of the young bulls. It turned out that sending preselected data, though based on genomic information, created bias in international evaluations, penalizing young bulls from the country sending the incorrect data. It also had an effect on the young bulls from the other countries. Sending biased data further affected the quality of international evaluations. This study underlines the importance of accounting for genomic preselection at the national level first. Moreover, submitting all available data appeared essential to maintain the quality of the international genetic evaluations after implementation of a genomic preselection step
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Impacts of genomic selection on classical genetic evaluations
No full textLes évaluations génomiques apportent une information précoce et suffisamment précise pour choisir les jeunes taureaux dans les schémas de sélection des bovins laitiers, incitant à remplacer le long processus de testage sur descendance par une étape de sélection génomique.Dès lors, seuls les candidats sélectionnés ont des filles avec performances et participent aux évaluations génétiques classiques. Cependant, toutes les informations ayant servi à la sélection ne sont plus incluses dans l’analyse et l’estimation des valeurs génétiques par la méthode du BLUP (Best Linear Unbiased Prediction) peut être incorrecte.Les évaluations génétiques classiques restent indispensables pour l’évaluation des animaux non génotypés, pour la comparaison des taureaux à l’échelle mondiale, et pour le calcul des futures prédictions génomiques. Compte-tenu de la rapide intégration de la génomique dans les schémas de sélection des bovins laitiers, il était important d’en étudier les conséquences sur les évaluations génétiques classiques.A l’échelle nationale, nos simulations ont montré que les valeurs génétiques des taureaux retenus sur information génomique étaient systématiquement sous-estimées et moins précises quand l’étape de sélection génomique n’était pas prise en compte dans le modèle statistique. Pour éviter ce biais, une méthode a été testée avec succès : pour l’ensemble des candidats à la sélection, des pseudo-performances sont calculées à partir des index génomiques et analysées par le BLUP. Suivant la prise en compte ou non de l’étape de sélection génomique, les pays participant aux évaluations internationales peuvent fournir des données biaisées et/ou incomplètes, au risque de pénaliser fortement leurs propres taureaux dans les classements internationaux. La diversité des pratiques à l’échelle mondiale et l’interaction des possibles sources de biais dans les évaluations internationales rendent sa propagation incontrôlable et fortement dommageable.Il est donc nécessaire et urgent d’adapter les évaluations génétiques classiques pour prendre en compte l’information génomique et ses pratiques associées. Diverses approches récentes sont discutées afin de proposer des alternatives faciles à mettre en place dans les centres d’évaluation, permettant de maintenir des évaluations non biaisées mais aussi plus précises.With the fast and wide development of genomic evaluations in dairy cattle, the design of breeding schemes has been modified and the long process of progeny testing is being replaced by an early and accurate genomic selection step.In the future, only selected candidates will get performances to be evaluated by the classical method of Best Linear Unbiased Prediction (BLUP). After a genomic selection step, information about the selection process is no longer complete, BLUP assumptions are violated and solutions, i.e., estimated breeding values, are feared to be incorrect.The aim of the thesis study was to consider the consequences of genomic selection on the classical genetic evaluations at the national and international levels.First, bias in national breeding values was assessed by repeated simulations. Estimated breeding values were systematically underestimated and less accurate after a genomic selection step not accounted for in genetic evaluation models.Secondly, a statistical procedure, a BLUP model with genomic pseudo-performances, was investigated to eliminate, with success, bias in estimated breeding values.In a third part, the consequences of genomic selection on international evaluations were studied by simulations. Bulls from the country sending incomplete and/or biased breeding values were the most penalized in international rankings.In conclusion, it is not only necessary but also urgent to prevent from bias in classical evaluations and therefore avoid harmful impacts on international comparisons, on future genomic evaluations, and more generally on selection efficiency. Alternative approaches were thus discussed to propose short and long term strategies for routine evaluations. Nevertheless, a main consequence of bias corrected breeding values is that all genetic predictions will include some genomic information in a near future: adaptations of evaluation methods are still required to optimally benefit from all types of information
Les impacts de la sélection génomique sur les évaluations génétiques classiques
No full textWith the fast and wide development of genomic evaluations in dairy cattle, the design of breeding schemes has been modified and the long process of progeny testing is being replaced by an early and accurate genomic selection step.In the future, only selected candidates will get performances to be evaluated by the classical method of Best Linear Unbiased Prediction (BLUP). After a genomic selection step, information about the selection process is no longer complete, BLUP assumptions are violated and solutions, i.e., estimated breeding values, are feared to be incorrect.The aim of the thesis study was to consider the consequences of genomic selection on the classical genetic evaluations at the national and international levels.First, bias in national breeding values was assessed by repeated simulations. Estimated breeding values were systematically underestimated and less accurate after a genomic selection step not accounted for in genetic evaluation models.Secondly, a statistical procedure, a BLUP model with genomic pseudo-performances, was investigated to eliminate, with success, bias in estimated breeding values.In a third part, the consequences of genomic selection on international evaluations were studied by simulations. Bulls from the country sending incomplete and/or biased breeding values were the most penalized in international rankings.In conclusion, it is not only necessary but also urgent to prevent from bias in classical evaluations and therefore avoid harmful impacts on international comparisons, on future genomic evaluations, and more generally on selection efficiency. Alternative approaches were thus discussed to propose short and long term strategies for routine evaluations. Nevertheless, a main consequence of bias corrected breeding values is that all genetic predictions will include some genomic information in a near future: adaptations of evaluation methods are still required to optimally benefit from all types of information.Les évaluations génomiques apportent une information précoce et suffisamment précise pour choisir les jeunes taureaux dans les schémas de sélection des bovins laitiers, incitant à remplacer le long processus de testage sur descendance par une étape de sélection génomique.Dès lors, seuls les candidats sélectionnés ont des filles avec performances et participent aux évaluations génétiques classiques. Cependant, toutes les informations ayant servi à la sélection ne sont plus incluses dans l’analyse et l’estimation des valeurs génétiques par la méthode du BLUP (Best Linear Unbiased Prediction) peut être incorrecte.Les évaluations génétiques classiques restent indispensables pour l’évaluation des animaux non génotypés, pour la comparaison des taureaux à l’échelle mondiale, et pour le calcul des futures prédictions génomiques. Compte-tenu de la rapide intégration de la génomique dans les schémas de sélection des bovins laitiers, il était important d’en étudier les conséquences sur les évaluations génétiques classiques.A l’échelle nationale, nos simulations ont montré que les valeurs génétiques des taureaux retenus sur information génomique étaient systématiquement sous-estimées et moins précises quand l’étape de sélection génomique n’était pas prise en compte dans le modèle statistique. Pour éviter ce biais, une méthode a été testée avec succès : pour l’ensemble des candidats à la sélection, des pseudo-performances sont calculées à partir des index génomiques et analysées par le BLUP. Suivant la prise en compte ou non de l’étape de sélection génomique, les pays participant aux évaluations internationales peuvent fournir des données biaisées et/ou incomplètes, au risque de pénaliser fortement leurs propres taureaux dans les classements internationaux. La diversité des pratiques à l’échelle mondiale et l’interaction des possibles sources de biais dans les évaluations internationales rendent sa propagation incontrôlable et fortement dommageable.Il est donc nécessaire et urgent d’adapter les évaluations génétiques classiques pour prendre en compte l’information génomique et ses pratiques associées. Diverses approches récentes sont discutées afin de proposer des alternatives faciles à mettre en place dans les centres d’évaluation, permettant de maintenir des évaluations non biaisées mais aussi plus précises
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Les impacts de la sélection génomique sur les évaluations génétiques classiques
No full textWith the fast and wide development of genomic evaluations in dairy cattle, the design of breeding schemes has been modified and the long process of progeny testing is being replaced by an early and accurate genomic selection step.In the future, only selected candidates will get performances to be evaluated by the classical method of Best Linear Unbiased Prediction (BLUP). After a genomic selection step, information about the selection process is no longer complete, BLUP assumptions are violated and solutions, i.e., estimated breeding values, are feared to be incorrect.The aim of the thesis study was to consider the consequences of genomic selection on the classical genetic evaluations at the national and international levels.First, bias in national breeding values was assessed by repeated simulations. Estimated breeding values were systematically underestimated and less accurate after a genomic selection step not accounted for in genetic evaluation models.Secondly, a statistical procedure, a BLUP model with genomic pseudo-performances, was investigated to eliminate, with success, bias in estimated breeding values.In a third part, the consequences of genomic selection on international evaluations were studied by simulations. Bulls from the country sending incomplete and/or biased breeding values were the most penalized in international rankings.In conclusion, it is not only necessary but also urgent to prevent from bias in classical evaluations and therefore avoid harmful impacts on international comparisons, on future genomic evaluations, and more generally on selection efficiency. Alternative approaches were thus discussed to propose short and long term strategies for routine evaluations. Nevertheless, a main consequence of bias corrected breeding values is that all genetic predictions will include some genomic information in a near future: adaptations of evaluation methods are still required to optimally benefit from all types of information.Les évaluations génomiques apportent une information précoce et suffisamment précise pour choisir les jeunes taureaux dans les schémas de sélection des bovins laitiers, incitant à remplacer le long processus de testage sur descendance par une étape de sélection génomique.Dès lors, seuls les candidats sélectionnés ont des filles avec performances et participent aux évaluations génétiques classiques. Cependant, toutes les informations ayant servi à la sélection ne sont plus incluses dans l’analyse et l’estimation des valeurs génétiques par la méthode du BLUP (Best Linear Unbiased Prediction) peut être incorrecte.Les évaluations génétiques classiques restent indispensables pour l’évaluation des animaux non génotypés, pour la comparaison des taureaux à l’échelle mondiale, et pour le calcul des futures prédictions génomiques. Compte-tenu de la rapide intégration de la génomique dans les schémas de sélection des bovins laitiers, il était important d’en étudier les conséquences sur les évaluations génétiques classiques.A l’échelle nationale, nos simulations ont montré que les valeurs génétiques des taureaux retenus sur information génomique étaient systématiquement sous-estimées et moins précises quand l’étape de sélection génomique n’était pas prise en compte dans le modèle statistique. Pour éviter ce biais, une méthode a été testée avec succès : pour l’ensemble des candidats à la sélection, des pseudo-performances sont calculées à partir des index génomiques et analysées par le BLUP. Suivant la prise en compte ou non de l’étape de sélection génomique, les pays participant aux évaluations internationales peuvent fournir des données biaisées et/ou incomplètes, au risque de pénaliser fortement leurs propres taureaux dans les classements internationaux. La diversité des pratiques à l’échelle mondiale et l’interaction des possibles sources de biais dans les évaluations internationales rendent sa propagation incontrôlable et fortement dommageable.Il est donc nécessaire et urgent d’adapter les évaluations génétiques classiques pour prendre en compte l’information génomique et ses pratiques associées. Diverses approches récentes sont discutées afin de proposer des alternatives faciles à mettre en place dans les centres d’évaluation, permettant de maintenir des évaluations non biaisées mais aussi plus précises
- …
