非亲缘样本的单标记关联分析

Single Marker Association Analysis for Unrelated Samples.

作者信息

Zheng Gang, Yuan Ao, Li Qizhai, Gastwirth Joseph L

机构信息

Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, 4000 Reservoir Rd. NW, Washington, DC, 20057, USA.

Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.

出版信息

Methods Mol Biol. 2017;1666:375-389. doi: 10.1007/978-1-4939-7274-6_18.

DOI:10.1007/978-1-4939-7274-6_18

PMID:28980255

Abstract

Methods for single marker association analysis are presented for binary and quantitative traits. For a binary trait, we focus on the analysis of retrospective case-control data using Pearson's chi-squared test, the trend test and a robust test. For a continuous trait, typical methods are based on a linear regression model or the analysis of variance. We illustrate how these tests can be applied using a publicly available R package "Rassoc" and some existing R functions. Guidelines for single-marker analysis are provided.

摘要

本文介绍了用于二元性状和定量性状的单标记关联分析方法。对于二元性状，我们着重于使用Pearson卡方检验、趋势检验和稳健检验对回顾性病例对照数据进行分析。对于连续性状，典型方法基于线性回归模型或方差分析。我们说明了如何使用公开可用的R包“Rassoc”和一些现有的R函数来应用这些检验。还提供了单标记分析的指南。