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

RVT1 has been proposed by Morris and Zeggini (2010) as a collapsing method based on a regression framework that models the phenotype as a function of a collapsed summary of the variants. More specifically, the considered summary in RVT1 is the proportion of rare variants that carry at least one copy of the minor allele. In this sense, RVT1 is an accumulation approach that regresses phenotype on a genetic score, defined as the proportion of sites within the gene that harbor mutations.

1 | ```
RVT1(y, X, maf = 0.05, perm = 100)
``` |

`y` |
numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed |

`X` |
numeric matrix or data frame with genotype data coded as 0, 1, 2. Missing data is allowed |

`maf` |
numeric value indicating the minor allele frequency threshold for rare variants ( |

`perm` |
positive integer indicating the number of permutations (100 by default) |

If no variants are below the specified `maf`

threshold, the function will stop and return an error message

There is no imputation for the missing data. Missing values are simply ignored in the computations.

An object of class `"assoctest"`

, basically a list with the following elements:

`rvt1.stat` |
rvt1 statistic |

`asym.pval` |
asymptotic p-value |

`perm.pval` |
permuted p-value |

`args` |
descriptive information with number of controls, cases, variants, rare variants, maf threshold, and permutations |

`name` |
name of the statistic |

Gaston Sanchez

Morris AP, Zeggini E (2010) An Evaluation of Statistical Approaches to Rare Variants Analysis in Genetic Association Studies. *Genetic Epidemiology*, **34**: 188-193

Asimit J, Zeggini E (2010) Rare Variant Association Analysis Methods for Complex Traits. *Annual Review of Genetics*, **44**: 293-308

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
## Not run:
# number of cases
cases = 500
# number of controls
controls = 500
# total (cases + controls)
total = cases + controls
# phenotype vector
phenotype = c(rep(1, cases), rep(0, controls))
# genotype matrix with 10 variants (random data)
set.seed(1234)
genotype = matrix(rbinom(total*10, 2, 0.051), nrow=total, ncol=10)
# apply RVT1 with maf=0.05 and 500 permutations
myrvt1 = RVT1(phenotype, genotype, maf=0.05, perm=500)
myrvt1
## End(Not run)
``` |

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