Description Usage Arguments Details Value Note Author(s) References See Also Examples

This function carries out tests for association between phenotype and a series of single nucleotide polymorphisms (SNPs), within strata defined by a possibly confounding factor. SNPs are considered one at a time and both 1-df and 2-df tests are calculated. For a binary phenotype, the 1-df test is the Cochran-Armitage test (or, when stratified, the Mantel-extension test).

1 | ```
single.snp.tests(phenotype, stratum, data = sys.parent(), snp.data, subset, snp.subset)
``` |

`phenotype` |
A vector containing the values of the phenotype |

`stratum` |
Optionally, a factor defining strata for the analysis |

`data` |
A dataframe containing the |

`snp.data` |
An object of class |

`subset` |
A vector or expression describing the subset of subjects
to be used in teh analysis. This is evaluated in the same
environment as the |

`snp.subset` |
A vector describing the subset of SNPs to be considered. Default action is to test all SNPs. |

Formally, the test statistics are score tests for generalized linear models with canonical link. That is, they are inner products between genotype indicators and the deviations of phenotypes from their stratum means. Variances (and covariances) are those of the permutation distribution obtained by randomly permuting phenotype within stratum.

The `subset`

argument can either be a logical vector of length
equal to the length of the vector of phenotypes, an integer vector
specifying positions in the `data`

frame, or a character vector
containing names of the selected rows in the `data`

frame. Similarly, the `snp.subset`

argument can be a logical,
integer, or character vector.

A dataframe, with columns

`chi2.1df` |
Cochran-Armitage type test for additive genetic component |

`chi2.2df` |
Chi-squared test for both additive and dominance components |

`N` |
The number of valid data points used |

The behaviour of this function for objects of class
`X.snp.matrix`

is as described by Clayton (2008). Males are
treated as homozygous females and corrected variance estimates are
used.

David Clayton [email protected]

Clayton (2008) Testing for association on the X chromosome
*Biostatistics* (In press)

1 2 3 4 5 6 7 | ```
data(testdata)
results <- single.snp.tests(cc, stratum=region, data=subject.data,
snp.data=Autosomes, snp.subset=1:10)
summary(results)
# QQ plot - see help(qq.chisq)
qq.chisq(results$chi2.1df)
qq.chisq(results$chi2.2df)
``` |

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