rankFactorsbyProfile {chroGPS} | R Documentation |
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.
rankFactorsbyProfile(x,minFactors=5,ranktype='glm',glm.threshold=0.5,verbose=TRUE,maxIter=ncol(x),mc.cores=1)
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. |
A data frame with the epigenetic factors in the order they are removed and their prediction accuracy.
Oscar Reina.
distGPS
, domainDist
, rankFactorsbyDomain
## 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)