期刊
BIOINFORMATICS
卷 30, 期 5, 页码 698-705出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt572
关键词
-
类别
资金
- NIH grants from the National Library of Medicine [LM010040]
- National Heart, Lung, and Blood via the Pharmacogenomics Research Network [HL065962]
- PGRN Statistical Analysis Resource (P-STAR)
- NIGMS [5T32GM080178]
Motivation: Advancements in high-throughput technology have allowed researchers to examine the genetic etiology of complex human traits in a robust fashion. Although genome-wide association studies have identified many novel variants associated with hundreds of traits, a large proportion of the estimated trait heritability remains unexplained. One hypothesis is that the commonly used statistical techniques and study designs are not robust to the complex etiology that may underlie these human traits. This etiology could include nonlinear gene x gene or gene x environment interactions. Additionally, other levels of biological regulation may play a large role in trait variability. Results: To address the need for computational tools that can explore enormous datasets to detect complex susceptibility models, we have developed a software package called the Analysis Tool for Heritable and Environmental Network Associations (ATHENA). ATHENA combines various variable filtering methods with machine learning techniques to analyze high-throughput categorical (i.e. single nucleotide polymorphisms) and quantitative (i.e. gene expression levels) predictor variables to generate multivariable models that predict either a categorical (i.e. disease status) or quantitative (i.e. cholesterol levels) outcomes. The goal of this article is to demonstrate the utility of ATHENA using simulated and biological datasets that consist of both single nucleotide polymorphisms and gene expression variables to identify complex prediction models. Importantly, this method is flexible and can be expanded to include other types of high-throughput data (i.e. RNA-seq data and biomarker measurements).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据