IDOLoptimize: IDOLoptimize
In immunomethylomics/IDOL: IDentifying Optimal DNA methylation Libraries (IDOL)

Description Usage Arguments Value

View source: R/IDOLoptimize.R

This function identifies optimal DML/DMR libraries for cell mixture deconvolution using the procedure described in Koestler et al., (2016).

1 2	IDOLoptimize(candDMRFinderObject, trainingBetas, trainingCovariates, libSize = 300, maxIt = 500, numCores = 4)

`candDMRFinderObject:`	List object returned from the CandidateDMRFinder.v2 function
`trainingBetas:`	A J x N matrix of beta-values where methylation was profiled in a heterogenous tissue type (i.e., WB). Here, J indicates the number of CpGs and N, the number of samples
`trainingCovariates:`	A N x P data.frame of meta data aross the N samples. Contained within the meta data must be the observed cell fractions (i.e. FACS or otherwise) for the K cell types indicated in the list object returned from the CandidateDMRFinder.v2 function. The naming of cell types should be consistent between these two objects as well.
`libSize:`	Size of the optimized IDOL library. Defaults to 300.
`maxIt:`	Maximum number of iterations for the IDOL algorithm. Defaults to 500.
`numCores:`	Number of processing cores to use (see R package DoParallel). Defaults to 4.

A list containing six objects: (1) "IDOL Optimized Library" - a vector containing the names of the CpGs in the identified IDOL optimized library (2) "IDOL Optimized CoefEsts" - matrix of the within-cell type mean methylation beta values across the CpGs in the optimal library (3) "RMSE" average root-mean squared error calculated across each iteration of IDOL (4) "R2" average R2 (coefficent of determinatino) calculated across each iteration of IDOL (5) "Number of iterations" how many iterations of IDOL were used (6) "Library Size" libsize above.

immunomethylomics/IDOL documentation built on July 9, 2020, 5:14 a.m.