train_model_gex: Train gene expression model from methylation profiles
In andreaskapou/BPRMeth-devel: Model higher-order methylation profiles

Description Usage Arguments Value Author(s) See Also Examples

train_model_gex trains a regression model for predicting gene expression levels by taking as input the higher order methylation features extracted from specific genomic regions.

1 2	train_model_gex(formula = NULL, model_name = "svm", train, is_summary = TRUE)

`formula`	An object of class `formula`, e.g. see `lm` function. If NULL, the simple linear regression model is used.
`model_name`	A string denoting the regression model. Currently, available models are: `"svm"`, `"randomForest"`, `"rlm"`, `"mars"` and `"lm"`.
`train`	The training data.
`is_summary`	Logical, print the summary statistics.

A list containing the following elements:

formula: The formula that was used.
gex_model: The fitted model.
train_pred The predicted values for the training data.
train_errors: The training error metrics.

C.A.Kapourani C.A.Kapourani@ed.ac.uk

predict_model_gex

# Create synthetic data
train_data <- data.frame(x = rnorm(20), y=rnorm(20, 1, 4))
res <- train_model_gex(formula = y~., train = train_data)

# Using a different model
res <- train_model_gex(model_name = "randomForest", train = train_data)