calculateSignificantLevel {methylInheritance} | R Documentation

## Calculate significant level for hypo and hyper conserved elements

### Description

Calculate significant level for hypo and hyper conserved elements using permutation results as well as observed results

### Usage

    calculateSignificantLevel(formatForGraphDataFrame)

### Arguments

`formatForGraphDataFrame` | a `data.frame` containing the observation results (using real data) and the permutation results (using shuffled data). Both hyper and hypo differentially conserved methylation results must be present. The `data.frame` must have 3 columns : "TYPE", "RESULT" and "SOURCE". The "TYPE" can be either "HYPER" or "HYPO". The "RESULT" is the number of conserved differentially elements. The "SOURCE" can be either "OBSERVATION" or "PERMUTATION".

### Value

a list containing two elements:

- `HYPER` a `double`, the significant level for the hyper differentially methylated conserved elements

- `HYPO` a `double`, the significant level for the hypo differentially methylated conserved elements

### Author(s)

Astrid Deschenes, Pascal Belleau

### Examples

    ## Loading dataset containing all results
    data(methylInheritanceResults)

    ## Extract information for the intersection between conserved differentially
    ## methylated sites (type = sites) between the intersection of 2
    ## generations (inter = i2): F2 and F3 (position = 2)
    info <- extractInfo(allResults = methylInheritanceResults,
        type = "sites", inter="i2", 2)

    ## Create graph
    methylInheritance:::calculateSignificantLevel(info)

[Package methylInheritance version 1.6.1 Index]