Single Marker Association Analysis for Unrelated Samples

  • Gang Zheng
  • Ao Yuan
  • Qizhai Li
  • Joseph L. Gastwirth
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1666)

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.

Key Words

Additive Association ANOVA Binary trait Case–control design Dominant Genetic model Genotype relative risks MAX3 Mode of inheritance Penetrance Rassoc Recessive Quantitative trait Robustness 

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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Gang Zheng
  • Ao Yuan
    • 1
  • Qizhai Li
    • 2
  • Joseph L. Gastwirth
    • 3
  1. 1.Department of Biostatistics, Bioinformatics and BiomathematicsGeorgetown UniversityWashington, DCUSA
  2. 2.Academy of Mathematics and Systems Science, Chinese Academy of SciencesBeijingChina
  3. 3.Department of StatisticsGeorge Washington UniversityWashington, DCUSA

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