Comparison of mixed-model approaches for association mapping.

@article{citeulike:2803517, abstract = {Association-mapping methods promise to overcome the limitations of linkage-mapping methods. The main objectives of this study were to (i) evaluate various methods for association mapping in the autogamous species wheat using an empirical data set, (ii) determine a marker-based kinship matrix using a restricted maximum-likelihood (REML) estimate of the probability of two alleles at the same locus being identical in state but not identical by descent, and (iii) compare the results of association-mapping approaches based on adjusted entry means (two-step approaches) with the results of approaches in which the phenotypic data analysis and the association analysis were performed in one step (one-step approaches). On the basis of the phenotypic and genotypic data of 303 soft winter wheat (Triticum aestivum L.) inbreds, various association-mapping methods were evaluated. Spearman's rank correlation between P-values calculated on the basis of one- and two-stage association-mapping methods ranged from 0.63 to 0.93. The mixed-model association-mapping approaches using a kinship matrix estimated by REML are more appropriate for association mapping than the recently proposed QK method with respect to (i) the adherence to the nominal alpha-level and (ii) the adjusted power for detection of quantitative trait loci. Furthermore, we showed that our data set could be analyzed by using two-step approaches of the proposed association-mapping method without substantially increasing the empirical type I error rate in comparison to the corresponding one-step approaches.}, address = {Institute for Plant Breeding, Seed Science, and Poulation Genetics, University of Hohenheim, Stuttgart, Germany.}, author = {Stich, B. and M\"{o}hring, J. and Piepho, H. P. and Heckenberger, M. and Buckler, E. S. and Melchinger, A. E. }, citeulike-article-id = {2803517}, doi = {10.1534/genetics.107.079707}, issn = {0016-6731}, journal = {Genetics}, month = {March}, number = {3}, pages = {1745--1754}, posted-at = {2008-05-16 02:51:13}, priority = {2}, title = {Comparison of mixed-model approaches for association mapping.}, url = {http://dx.doi.org/10.1534/genetics.107.079707}, volume = {178}, year = {2008} }

TY - JOUR ID - citeulike:2803517 L3 - citeulike-article-id:2803517 TI - Comparison of mixed-model approaches for association mapping. JF - Genetics VL - 178 IS - 3 SP - 1745 EP - 1754 AD - Institute for Plant Breeding, Seed Science, and Poulation Genetics, University of Hohenheim, Stuttgart, Germany. SN - 0016-6731 N2 - Association-mapping methods promise to overcome the limitations of linkage-mapping methods. The main objectives of this study were to (i) evaluate various methods for association mapping in the autogamous species wheat using an empirical data set, (ii) determine a marker-based kinship matrix using a restricted maximum-likelihood (REML) estimate of the probability of two alleles at the same locus being identical in state but not identical by descent, and (iii) compare the results of association-mapping approaches based on adjusted entry means (two-step approaches) with the results of approaches in which the phenotypic data analysis and the association analysis were performed in one step (one-step approaches). On the basis of the phenotypic and genotypic data of 303 soft winter wheat (Triticum aestivum L.) inbreds, various association-mapping methods were evaluated. Spearman's rank correlation between P-values calculated on the basis of one- and two-stage association-mapping methods ranged from 0.63 to 0.93. The mixed-model association-mapping approaches using a kinship matrix estimated by REML are more appropriate for association mapping than the recently proposed QK method with respect to (i) the adherence to the nominal alpha-level and (ii) the adjusted power for detection of quantitative trait loci. Furthermore, we showed that our data set could be analyzed by using two-step approaches of the proposed association-mapping method without substantially increasing the empirical type I error rate in comparison to the corresponding one-step approaches. AU - Stich, B AU - Möhring, J AU - Piepho, HP AU - Heckenberger, M AU - Buckler, ES AU - Melchinger, AE PY - 2008/03// UR - http://dx.doi.org/10.1534/genetics.107.079707 ER -