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Single marker association analysis for unrelated samples.

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 public available R package "Rassoc" and some existing R functions. Guidelines for choosing these test statistics are provided.

SUBMITTER: Zheng G

PROVIDER: S-EPMC3652252 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Single marker association analysis for unrelated samples.

Zheng Gang G Xu Jinfeng J Yuan Ao A Gastwirth Joseph L JL

Methods in molecular biology (Clifton, N.J.) 20120101

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 public available R package "Rassoc" and some existing R functions. Guidelines for choosing th ...[more]

PMID: 22307707

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