Wang Hui, Rose Sherri, van der Laan Mark J
University of California, Berkeley, School of Public Health, Division of Biostatistics, 101 Haviland Hall, #7358, Berkeley, CA 94720, USA.
Stat Probab Lett. 2011 Jul 1;81(7):792-796. doi: 10.1016/j.spl.2010.11.001.
Quantitative trait loci mapping is focused on identifying the positions and effect of genes underlying an an observed trait. We present a collaborative targeted maximum likelihood estimator in a semi-parametric model using a newly proposed 2-part super learning algorithm to find quantitative trait loci genes in listeria data. Results are compared to the parametric composite interval mapping approach.
数量性状基因座定位专注于识别潜在观察性状的基因的位置和效应。我们在半参数模型中提出了一种协作式靶向最大似然估计器，使用新提出的两部分超级学习算法在李斯特菌数据中寻找数量性状基因座基因。将结果与参数复合区间定位方法进行比较。
