Enhancing genome-enabled prediction by bagging genomic BLUP

PLoS ONE

Volumn 9, Issue 4, 2014, Pages

  Gianola, Daniel ^a,b   Weigel, Kent A ^a   Krämer, Nicole ^c   Stella, Alessandra ^d   Schön, Chris Carolin ^c  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^d PARCO TECNOLOGICO PADANO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BOOTSTRAP AGGREGATING SAMPLING; BOOTSTRAPPING; GENETIC ALGORITHM; GENOMIC BEST LINEAR UNBIASED PREDICTION; GRAIN YIELD; MACHINE LEARNING; MEASUREMENT ACCURACY; QUANTITATIVE TRAIT LOCUS; SIMULATION; STATISTICAL MODEL; VALIDATION STUDY; WHEAT; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; GENETIC MARKER; GENETICS; GENOME; GENOMICS; GENOTYPE; PHENOTYPE; PREDICTIVE VALUE; PROCEDURES; QUANTITATIVE TRAIT; REGRESSION ANALYSIS; REPRODUCIBILITY; SAMPLE SIZE;

GENETIC MARKER;

ALGORITHMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENETIC MARKERS; GENOME; GENOMICS; GENOTYPE; LEAST-SQUARES ANALYSIS; LINEAR MODELS; MODELS, GENETIC; PHENOTYPE; PREDICTIVE VALUE OF TESTS; QUANTITATIVE TRAIT LOCI; QUANTITATIVE TRAIT, HERITABLE; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; TRITICUM;

EID: 84899528042     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0091693     Document Type: Article

References (45)

1. Van Raden PM (2008) Efficient methods to compute genomic predictions. Journal of Dairy Science 91:4414-4423.
2. VanRaden PM, Van Tassell CP, Wiggans GR, Sonstegard TS, Schnabel RD, et al. (2009) Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science 92:16-24.
3. Henderson CR (1976) A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding value. Biometrics 32:69-83.
4. Nejati-Javaremi A, Smith C, Gibson J (1997) Effect of total allelic relationship on accuracy of evaluation and response to selection. Journal of Animal Science 75:1738-1745. (Pubitemid 127444988)
5. Astle W, Balding DJ (2009) Population structure and cryptic relatedness in genetic association studies. Statistical Science 4:451-471.
6. Forni S, Aguilar I, Misztal I (2011) Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. Genetics, Selection, Evolution 43: 1.
7. de los Campos G, Vazquez AI, Fernando R, Klimentidis YC, Sorensen D (2013) Prediction of complex human traits using the genomic best linear unbiased predictor. PLOS Genetics 9 e1003608.
8. Henderson CR (1973) Sire Evaluation and Genetic Trends. Proceedings of the Animal Breeding and Genetics Symposium in Honor of Dr. Jay L. Lush, 10-41, Champaign: American Society of Animal Science and the American Dairy Science Association.
9. Henderson CR (1977) Best linear unbiased prediction of breeding values not in the model for records. Journal of Dairy Science 60:783-787.
10. Henderson CR (1984) Application of Linear Models in Animal Breeding, Guelph: University of Guelph.
11. Habier D, Fernando RL, Dekkers JCM (2007) The impact of genetic relationship Information on genome-assisted breeding values. Genetics 177:2389-2397. (Pubitemid 350277013)
12. Goddard ME (2008) Genomic selection: prediction of accuracy and maximisation of long term response. Genetica Epub PMID: 18704696.
13. Janss L, de los Campos G, Sheehan N, Sorensen D (2012) Inferences from genomic models in stratified populations. Genetics 92: 693-704.
14. de los Campos G, Gianola D, Rosa GJM (2009) Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation. Journal of Animal Science 87:1883-1887.
15. Gianola D, Fernando RL, Stella A (2006) Genomic assisted prediction of genetic value with semi-parametric procedures. Genetics 173:1761-1776. (Pubitemid 44127674)
16. Gianola D, van Kaam JBCHM (2008) Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits 178(4): 2289-2303.
17. Gianola D, Okut H, Weigel KA, Rosa GJM (2011) Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat. BMC Genetics 2011 12:87 doi:10.1186/1471-2156-12-87.
18. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819-1829. (Pubitemid 32298846)
19. Gianola D (2013) Priors in whole-genome regression: the Bayesian alphabet returns. Genetics 194:573-596.
20. Ober U, Ayroles JF, Stone EA, Richards S, Zhu D, et al. (2012) Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster. PLos Genetics 8 e1002685.
21. Heslot N, Yang HP, Sorrells ME, Jannink JL (2012) Genomic selection in plant breeding: a comparison of models. Crop Science 52:146-160.
22. Ogutu JO, Schulz-Streeck T, Piepho HP (2012) Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions. BMC Proceedings 6 (Suppl 2): S10. http://www.biomedcentral. com/1753-6561/6/S2/S10
23. Wimmer V, Lehermeier C, Albrecht T, Auinger HJ, Wang Y, et al. (2013) Genome-wide prediction of traits with different genetic architecture through efficient variable selection. Genetics 195:573-587.
24. Lehermeier C, Wimmer V, Albrecht T, Auinger H, Gianola D, et al. (2012) Sensitivity to prior specification in Bayesian genome-based prediction models. Statistical Applications in Genetics and Molecular Biology 12: 375-391. doi:10.1515/sagmb-2012-0042.
25. Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, et al. (2010) A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science 93:743-752.
26. de los Campos G, Gianola D, Allison DAB (2010) Predicting genetic predisposition in humans: the promise of whole-genome markers. Nature Reviews Genetics 11:880-886.
27. Daetwyler HD, Villanueva B, Woolliams JA (2008) Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS One 3: e3395.
28. Daetwyler HD, Hickey JM, Henshall JM, Dominik S, Gredler B, et al. (2010) Accuracy of estimated genomic breeding values for wool and meat traits in a multi-breed sheep population. Animal Production Science 50:1004-1010.
29. Erbe M, Pimentel ECG, Sharifi AR, Simianer H (2010) Assessment of Cross-validation Strategies for Genomic Prediction in Cattle. Book of Abstracts of the 9th WCGALP, S. 129. Leipzig, Germany.
30. Erbe M (2013) Accuracy of genomic prediction in dairy cattle. PhD Thesis, George-August University, Göttingen, Germany.
31. Breiman L (1996) Bagging predictors. Machine Learning 24:123-140.
32. Breiman L (2001a) Using iterated bagging to debias regressions. Machine Learning 45:261-277.
33. Suen Y-L, Melville P, Mooney RJ (2005) Combining bias and variance reduction techniques for regression trees. Proceedings of the 16th European Conference on Machine Learning. pp. 741-749. Porto, Portugal.
34. Valle C, Nanculef R, Allende H, Moraga C (2007) Two bagging algorithms with coupled learners to encourage diversity. In: Berthold MR, Shawe-Taylor J, Lavrac N, editors. Advances in Intelligent Data Analysis VII. LNCS 4723, pp. 130-139.
35. Gianola D, Foulley JL (1999) Variance estimation from integrated likelihoods (VEIL). Genetics, Selection, Evolution 22:403-417.
36. Falconer DS, Mackay TFC (1996) Introduction to Quantitative Genetics. Ed. 4. Longmans Green, Harlow, Essex, UK.
37. Inoue A, Kilian L (2008) How useful is bagging in forecasting economic time series? A case study of U.S. Consumer Price Inflation. Journal of the American Statistical Association 103:511-522.
38. Breiman L (2001b) Random Forests. Machine Learning 45:5-32.
39. Bulmer MG (1980) The Mathematical Theory of Quantitative Genetics, Oxford: Oxford University Press.
40. Fernando RL, Gianola D (1986) Optimal properties of the conditional mean as a selection criterion. Theoretical and Applied Genetics 72: 822-825.
41. Casella G, George EI (1992) Explaining the Gibbs Sampler. The American Statistician 46:167-174.
42. Crossa J, de Los Campos G, Pérez P, Gianola D, Burgueño J, et al. (2010) Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713-724.
43. Long N, Gianola D, Rosa GJM, Weigel KA (2011) Marker-assisted prediction of non-additive genetic values. Genetica 139:843-854.
44. Takezawa K (2006) Introduction to Non-parametric Regression. Wiley-Interscience, Hoboken.
45. Makowsky R, Pajewski NM, Klimentidis YC, Vázquez AI, Duarte CW, et al. (2011) Beyond missing heritability: prediction of complex traits. PLoS Genetics doi:10.1371/journal.pgen.1002051.