# function for testing a single/pooled variant for continuous traits with family data using generalized linear mixed effects model

### Description

Fit generalized linear mixed effects model (GLMM) with logistic link
that treats each pedigree as a cluster to test a single/pooled variant for
associations against a continuous phenotype with family data. The `glmer`

function from package `lme4`

is used.

### Usage

1 | ```
glmm.EC(snp,phen,test.dat,covar,chr)
``` |

### Arguments

`snp` |
a numeric vector with genotype of a single/pooled variant |

`phen` |
a character string for the phenotype name of a binary trait of
interest in |

`test.dat` |
the product of merging phenotype, genotype and pedigree data, should be ordered by "famid" |

`covar` |
a character vector for covariates in |

`chr` |
chromosome number |

### Details

The `glmm.EC`

function fits a generalized linear mixed effects model (GLMM)
with logistic link that treats each pedigree as a cluster to test association between
a binary trait and a single/pooled genetic variant with additive model. The
trait-variant association test is carried out by the `glmer`

function from package
`lme4`

. P-value from likelihood ratio test (LRT) is reported. This function is
called in `glmm.ped`

function to test all single/pooled variants.

### Value

`ntotal ` |
number of individuals with genotype, phenotype and covariates |

`nmiss ` |
number of individuals with missing genotype among |

`maf_ntotal ` |
minor allele frequency based on |

`beta ` |
regression coefficient of single SNP test or burden test |

`se ` |
standard error of |

`Z ` |
Z statistic based on signed LRT |

`remark ` |
additional information of the analysis |

`p ` |
LRT p-value of a single variant test or burden test |

`MAC ` |
minor allele count |

`n0 ` |
the number of individuals with 0 copy of coded alleles |

`n1 ` |
the number of individuals with 1 copy of coded alleles |

`n2 ` |
the number of individuals with 2 copies of coded alleles |

### Author(s)

Ming-Huei Chen <mhchen@bu.edu> and Qiong Yang <qyang@bu.edu>

### References

Bates D, Maechler M, Bolker B and Walker S (2014). lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-7, http://CRAN.R-project.org/package=lme4.

### Examples

1 2 3 4 5 |