trainMediator.RdThe function trains a predictive model of a given mediator and then predicts the genetically regulated intensity of it in the training set via cross-validation.
trainMediator( medInt, pheno = NULL, mediator, medLocs, snps, snpLocs, covariates, seed, k, cisDist = 5e+05, prune = T, windowSize = 50, numSNPShift = 5, ldThresh = 0.5, snpAnnot = NULL )
| medInt | character, identifier for mediator of interest |
|---|---|
| mediator | data frame, mediator intensities |
| medLocs | data frame, MatrixEQTL locations for mediators |
| snps | data frame, SNP dosages |
| snpLocs | data frame, MatrixEQTL locations for SNPs |
| covariates | data frame, covariates |
| seed | integer, random seed for splitting |
| k | integer, number of training-test splits |
| prune | logical, TRUE/FALSE to LD prune the genotypes |
| windowSize | integer, window size for PLINK pruning |
| numSNPShift | integer, shifting window for PLINK pruning |
| ldThresh | numeric, LD threshold for PLINK pruning |
| parallel | logical, TRUE/FALSE to run glmnet in parallel |
| cores | integer, number of parallel cores |
final model for mediator along with CV R2 and predicted values