Pan Wei
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455-0378, USA.
Bioinformatics. 2009 Jun 1;25(11):1390-6. doi: 10.1093/bioinformatics/btp177. Epub 2009 Mar 31.
We consider the problem of multiple locus linkage analysis for expression traits of genes in a pathway or a network. To capitalize on co-expression of functionally related genes, we propose a penalized regression method that maps multiple expression quantitative trait loci (eQTLs) for all related genes simultaneously while accounting for their shared functions as specified a priori by a gene pathway or network.
An analysis of a mouse dataset and simulation studies clearly demonstrate the advantage of the proposed method over a standard approach that ignores biological knowledge of gene networks.
我们考虑对通路或网络中基因的表达性状进行多位点连锁分析的问题。为了利用功能相关基因的共表达，我们提出了一种惩罚回归方法，该方法可以同时绘制所有相关基因的多个表达数量性状位点（eQTL），同时考虑到由基因通路或网络先验指定的它们的共享功能。
对小鼠数据集的分析和模拟研究清楚地证明了所提出的方法相对于忽略基因网络生物学知识的标准方法的优势。
