Conduct multiple quantitative trait loci (QTL) mapping under the framework of random-QTL-effect linear mixed model. First, each position on the genome is detected in order to obtain a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve are viewed as potential QTL, all the effects of the potential QTL are included in a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid population or by adaptive lasso in F2 population, and true QTL are identified by likelihood radio test. See Wen et al. (2018) <doi:10.1093/bib/bby058>.
Version: 2.1.1 Depends: R (≥ 3.5.0), shiny, MASS, qtl Imports: Rcpp (≥ 0.12.17), methods, openxlsx, stringr, data.table, glmnet, doParallel, foreach, QTL.gCIMapping LinkingTo: Rcpp Published: 2020-10-12 DOI: 10.32614/CRAN.package.QTL.gCIMapping.GUI Author: Zhang Ya-Wen, Wen Yang-Jun, Wang Shi-Bo, and Zhang Yuan-Ming Maintainer: Yuanming Zhang <soyzhang at mail.hzau.edu.cn> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: yes CRAN checks: QTL.gCIMapping.GUI results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=QTL.gCIMapping.GUI to link to this page.
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