Packaged: 2016-03-06 02:50:34 UTC; Administrator

Author: Wenlong Ren,Shibo Wang,Bo Huang and Yuanming Zhang
Packaged: 2016-04-07 13:03:25 UTC; Administrator

Author: Wenlong Ren,Yuanli Ni Shibo Wang,Bo Huang and Yuanming Zhang
Description: Conduct multi-locus random-SNP-effect mixed linear model analysis for genome-wide association study and linkage analysis. First, each position (or marker) on the genome is scanned using random-SNP-effect mixed linear model method. Then, all the markers (or putative QTL) selected from the first step are included in the multi-locus model and their effects are estimated by an EM empirical Bayes method. Bonferroni correction is replaced by a less stringent selection criterion for significance test.

Title: Multi-Locus Random-SNP-Effect Mixed Linear Model for Genome-Wide
Association Studies and Linkage Analyses
Author: Wenlong Ren,Yuanli Ni,Shibo Wang,Yangjun Wen,Bo Huang and Yuanming Zhang
Description: Conduct multi-locus GWAS and multi-locus QTL mapping under the framework of random-SNP-effect mixed linear model (mrMLM). First, each position (or marker) on the genome is scanned by mrMLM algorithm. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers (or QTL) that are potentially associated with the trait are included in a multi-locus model, their effects are estimated by empirical Bayes and true QTN or QTL are identified by likelihood ratio test.

Packaged: 2017-02-08 14:47:04 UTC; Administrator

Title: Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for
Author: Zhang Ya-Wen, Li Pei, Ren Wen-Long, Ni Yuan-Li, and Zhang Yuan-Ming
Description: Conduct multi-locus genome-wide association study under the framework of random-SNP-effect mixed linear model (mrMLM). First, each marker on the genome is scanned. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers that are potentially associated with the trait are included in a multi-locus model, their effects are estimated by empirical Bayes and true QTN are identified by likelihood ratio test.