Selecting Informative Traits for Multivariate Quantitative Trait Locus Mapping Helps to Gain Optimal Power

被引:6
作者
Cheng, Riyan [1 ]
Borevitz, Justin [1 ]
Doerge, R. W. [2 ]
机构
[1] Australian Natl Univ, Res Sch Biol, Div Plant Sci, Canberra, ACT 0200, Australia
[2] Purdue Univ, Dept Stat, W Lafayette, IN 47907 USA
来源
GENETICS | 2013年 / 195卷 / 03期
关键词
quantitative trait locus (QTL); multitrait mapping; variable selection; statistical power; MARKER-FACILITATED INVESTIGATIONS; LINKAGE ANALYSIS; GENETIC-MARKERS; LEAST-SQUARES; ARABIDOPSIS; EXPRESSION; COMPLEXES; VARIABLES; MAIZE;
D O I
10.1534/genetics.113.155937
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
A major consideration in multitrait analysis is which traits should be jointly analyzed. As a common strategy, multitrait analysis is performed either on pairs of traits or on all of traits. To fully exploit the power of multitrait analysis, we propose variable selection to choose a subset of informative traits for multitrait quantitative trait locus (QTL) mapping. The proposed method is very useful for achieving optimal statistical power for QTL identification and for disclosing the most relevant traits. It is also a practical strategy to effectively take advantage of multitrait analysis when the number of traits under consideration is too large, making the usual multivariate analysis of all traits challenging. We study the impact of selection bias and the usage of permutation tests in the context of variable selection and develop a powerful implementation procedure of variable selection for genome scanning. We demonstrate the proposed method and selection procedure in a backcross population, using both simulated and real data. The extension to other experimental mapping populations is straightforward.
引用
收藏
页码:683 / +
页数:26
相关论文
共 30 条
[1]  
Cheng R., 2007, THESIS PURDUE U W LA
[2]   A Simulation Study of Permutation, Bootstrap, and Gene Dropping for Assessing Statistical Significance in the Case of Unequal Relatedness [J].
Cheng, Riyan ;
Palmer, Abraham A. .
GENETICS, 2013, 193 (03) :1015-+
[3]   Expression Quantitative Trait Loci Mapping With Multivariate Sparse Partial Least Squares Regression [J].
Chun, Hyonho ;
Keles, Suenduez .
GENETICS, 2009, 182 (01) :79-90
[4]  
CHURCHILL GA, 1994, GENETICS, V138, P963
[5]  
EDWARDS MD, 1987, GENETICS, V116, P113
[6]   Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease [J].
Hubner, N ;
Wallace, CA ;
Zimdahl, H ;
Petretto, E ;
Schulz, H ;
Maciver, F ;
Mueller, M ;
Hummel, O ;
Monti, J ;
Zidek, V ;
Musilova, A ;
Kren, V ;
Causton, H ;
Game, L ;
Born, G ;
Schmidt, S ;
Müller, A ;
Cook, SA ;
Kurtz, TW ;
Whittaker, J ;
Pravenec, M ;
Aitman, TJ .
NATURE GENETICS, 2005, 37 (03) :243-253
[7]  
JIANG CJ, 1995, GENETICS, V140, P1111
[8]  
KIM K, 2007, THESIS PURDUE U W LA
[9]   Genomic survey of gene expression diversity in Arabidopsis thaliana [J].
Kliebenstein, DJ ;
West, MAL ;
van Leeuwen, H ;
Kim, K ;
Doerge, RW ;
Michelmore, RW ;
St Clair, DA .
GENETICS, 2006, 172 (02) :1179-1189
[10]  
Knott SA, 2000, GENETICS, V156, P899