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  1. Journal of Agricultural, Biological, and Environmental Statistics
  2. Journal of Agricultural, Biological, and Environmental Statistics : Volume 16
  3. Journal of Agricultural, Biological, and Environmental Statistics : Volume 16, Issue 2, June 2011
  4. Identifying QTLs and Epistasis in Structured Plant Populations Using Adaptive Mixed LASSO
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Journal of Agricultural, Biological, and Environmental Statistics : Volume 22
Journal of Agricultural, Biological, and Environmental Statistics : Volume 21
Journal of Agricultural, Biological, and Environmental Statistics : Volume 20
Journal of Agricultural, Biological, and Environmental Statistics : Volume 19
Journal of Agricultural, Biological, and Environmental Statistics : Volume 18
Journal of Agricultural, Biological, and Environmental Statistics : Volume 17
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16, Issue 4, December 2011
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16, Issue 3, September 2011
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16, Issue 2, June 2011
Comparison of Models for Olfactometer Data
Identifying QTLs and Epistasis in Structured Plant Populations Using Adaptive Mixed LASSO
Nonparametric Threshold Model of Zero-Inflated Spatio-Temporal Data with Application to Shifts in Jellyfish Distribution
Statistical Modelling of Neighbor Treatment Effects in Aquaculture Clinical Trials
An EM Algorithm for Fitting a Four-Parameter Logistic Model to Binary Dose-Response Data
Spatial Regression Using Kernel Averaged Predictors
Full Open Population Capture–Recapture Models With Individual Covariates
Joint Modeling of Spatial Variability and Within-Row Interplot Competition to Increase the Efficiency of Plant Improvement
Functional Data Analysis in Ecosystem Research: The Decline of Oweekeno Lake Sockeye Salmon and Wannock River Flow
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16, Issue 1, March 2011
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15
Journal of Agricultural, Biological, and Environmental Statistics : Volume 14
Journal of Agricultural, Biological, and Environmental Statistics : Volume 13
Journal of Agricultural, Biological, and Environmental Statistics : Volume 12
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11
Journal of Agricultural, Biological, and Environmental Statistics : Volume 10
Journal of Agricultural, Biological, and Environmental Statistics : Volume 9
Journal of Agricultural, Biological, and Environmental Statistics : Volume 8
Journal of Agricultural, Biological, and Environmental Statistics : Volume 7
Journal of Agricultural, Biological, and Environmental Statistics : Volume 6

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Identifying QTLs and Epistasis in Structured Plant Populations Using Adaptive Mixed LASSO

Content Provider Springer Nature Link
Author Wang, Dong Eskridge, Kent M. Crossa, Jose
Copyright Year 2010
Abstract Association analysis in important crop species has generated heightened interest for its potential in dissecting complex traits by utilizing diverse mapping populations. However, the mixed linear model approach is currently limited to single marker analysis, which is not suitable for studying multiple QTL effects, epistasis and gene by environment interactions. In this paper, we propose the adaptive mixed LASSO method that can incorporate a large number of predictors (genetic markers, epistatic effects, environmental covariates, and gene by environment interactions) while simultaneously accounting for the population structure. We show that the adaptive mixed LASSO estimator possesses the oracle property of adaptive LASSO. Algorithms are developed to iteratively estimate the regression coefficients and variance components. Our results demonstrate that the adaptive mixed LASSO method is very promising in modeling multiple genetic effects when a large number of markers are available and the population structure cannot be ignored. It is expected to be a powerful tool for studying the architecture of complex traits in important plant species. Supplemental materials for this article are available from the journal website.
Starting Page 170
Ending Page 184
Page Count 15
File Format PDF
ISSN 10857117
Journal Journal of Agricultural, Biological, and Environmental Statistics
Volume Number 16
Issue Number 2
e-ISSN 15372693
Language English
Publisher Springer-Verlag
Publisher Date 2010-10-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Association analysis Oracle property Penalized regression Plant breeding Shrinkage estimation Environmental Monitoring/Analysis Agriculture Statistics for Life Sciences, Medicine, Health Sciences Biostatistics
Content Type Text
Resource Type Article
Subject Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty
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