rankFactorsbyProfile {chroGPS} | R Documentation

## Function to help selecting candidate epigenetic factors based on their predictive capabilities.

### Description

Function to help selecting candidate epigenetic factors based on their predictive capabilities. This function evaluates how information from a certain set of epigenetic factors can be used to accurately predict information from the rest using linear and logistic regression.

### Usage

    rankFactorsbyProfile(x,minFactors=5,ranktype='glm',glm.threshold=0.5,verbose=TRUE,maxIter=ncol(x),mc.cores=1)

### Arguments

`x` | A genes x factors table as used in the distGPS function for generation of epigenetic gene maps.
`minFactors` | Minimum set of 'core' factors to retain. Factors are removed based on how accurately they can be predicted by others.
`ranktype` | Either 'lm' for using linear regression, or 'glm' for logistic.
`glm.threshold` | For 'glm', threshold to round values obtained from the predict function so that they are compared with the real values. Defaults to 0.5.
`verbose` | Informs about progression of the linear or logistic regression steps.
`maxIter` | Deprecated.
`mc.cores` | Cores to use in calls to parallel::mclapply.

### Value

A data frame with the epigenetic factors in the order they are removed and their prediction accuracy.

### Author(s)

Oscar Reina.

### See Also

`distGPS`, `domainDist`, `rankFactorsbyDomain`

### Examples

    ## Not run

    data(s2)

    # Unknown domains
    # Perform computation
    glm.rank <- rankFactorsbyProfile(s2.tab,ranktype='glm',glm.threshold=0.75,mc.cores=1)

    # Returned objects are lists named by the factor with highest prediction accuracy in each iteration
    names(glm.rank)

[Package chroGPS version 2.4.0 Index]