Sparse regression models for unraveling group and individual associations in eQTL mapping.
Sparse regression models for unraveling group and individual associations in eQTL mapping.
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DOI：
10.1186/s12859-016-0986-9
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发表时间：
2016-03-22
影响因子：
3
通讯作者：
Wang W
中科院分区：
文献类型：
--
作者：
Cheng W;Shi Y;Zhang X;Wang W
表达数量性状基因座（expression quantitative trait loci，eQTL）研究作为揭示常见疾病遗传基础的有效工具，已引起人们越来越多的关注。传统的eQTL方法主要研究单个单核苷酸多态性（single nucleotide polymorphisms，SNPs）与基因表达性状之间的关系。这种方法的一个主要缺点是它不能模拟一组SNP对一组基因的联合作用，这可能对应于生物学途径。为了缓解这一限制，在本文中，我们提出了geQTL，稀疏回归方法，可以检测组明智的和个人之间的关联SNPs和表达性状。geQTL还可以校正潜在混杂因素的影响。我们的方法采用计算效率高的技术，因此它能够满足大规模的研究。此外，我们的方法可以自动推断适当数量的组明智的协会。我们在模拟数据集和酵母数据集上进行了大量的实验，以证明所提出的方法的有效性和效率。结果表明，geQTL可以有效地检测个体和群体的明智的信号，并优于国家的最先进的大幅度。这一研究结果很好地说明了将个体关联和群体关联解耦进行关联作图可以提高eQTL定位的准确性，并推断个体关联和群体关联。本文的在线版本（doi：10.1186/s12859-016-0986-9）包含补充材料，可供授权用户使用。
As a promising tool for dissecting the genetic basis of common diseases, expression quantitative trait loci (eQTL) study has attracted increasing research interest. Traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to biological pathways. To alleviate this limitation, in this paper, we propose geQTL, a sparse regression method that can detect both group-wise and individual associations between SNPs and expression traits. geQTL can also correct the effects of potential confounders. Our method employs computationally efficient technique, thus it is able to fulfill large scale studies. Moreover, our method can automatically infer the proper number of group-wise associations. We perform extensive experiments on both simulated datasets and yeast datasets to demonstrate the effectiveness and efficiency of the proposed method. The results show that geQTL can effectively detect both individual and group-wise signals and outperforms the state-of-the-arts by a large margin. This paper well illustrates that decoupling individual and group-wise associations for association mapping is able to improve eQTL mapping accuracy, and inferring individual and group-wise associations. The online version of this article (doi:10.1186/s12859-016-0986-9) contains supplementary material, which is available to authorized users.