runBumphunter {MEAL} | R Documentation

## Run bumphunter

### Description

Run bumphunter to a methylation dataset. This function contains all steps of bumphunter analysis, from model.matrix creation to running the analysis.

### Usage

    runBumphunter(set, model, coefficient = 2, bumphunter_cutoff = 0.1,
      num_permutations = 0, bumps_max = 30000, betas = TRUE,
      check_perms = FALSE, verbose = FALSE, resultSet = FALSE, ...)

### Arguments

`set` | `GenomicRatioSet`, `eSet` derived object or `SummarizedExperiment`
`model` | Model matrix or formula to get model matrix from `set`.
`coefficient` | Numeric with the column of model matrix used in the analysis. (Default: 2)
`bumphunter_cutoff` | Numeric with the minimum cutoff to include a probe in a block. (Default: 0.1)
`num_permutations` | Numeric with the number of permutations run to compute the bumps p-value. (Default: 0)
`bumps_max` | Numeric with the maximum number of bumps used in the permutation. This parameter only applies when `num_permutations` is greater than 0. (Default: 30000)
`betas` | If `set` is a `GenomicRatioSet`, should beta values be used? (Default: TRUE)
`check_perms` | Logical. Should we check that there are less bumps than `bumps_max`? This parameter only applies when `num_permutations` is greater than 0. (Default: TRUE)
`verbose` | Logical value. Should the function be verbose? (Default: FALSE)
`resultSet` | Should results be encapsulated in a `resultSet`? (Default: TRUE)
`...` | Further arguments passed to `bumphunter`.

### Details

runBumphunter is a wrapper for minfi `bumphunter`. This function runs all the steps required prior running bumphunter from the methylation set and the formula of the model. This implementation allows running bumphunter to other objects than `GenomicRatioSet`. The result can be encapsulated in a `ResultSet` to take adavantege of its plotting capabilities.

If the user wants to run permutations to calculate p-values, this implementation can filter the bumps to avoid doing a very high number of permutations and to reduce computation time. To do so, we can set the maximum number of bumps that we want to permute with the `bumps_max` parameter. runBumphunter increases `bumphunter_cutoff` value until the number of bumps is lower than `bumps_max`.

### Value

data.frame or `resultSet` with the result of `bumphunter`

### See Also

`bumphunter`

[Package MEAL version 1.10.1 Index]