rankFactorsbyProfile: Function to help selecting candidate epigenetic factors based...

Description Usage Arguments Value Author(s) See Also Examples

View source: R/rankFactorsbyProfile.R

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

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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

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## 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)

chroGPS documentation built on Oct. 31, 2019, 4:52 a.m.