train_continuous_model {CoRegFlux} | R Documentation |
Train a linear model and predict the gene expression from an experiment influence
train_continuous_model(train_expression, train_influence, minTarget = 10, experiment_influence, network)
train_expression |
Gene expression of the training data set, not necessary if train_influence is supplied. Should be numerical matrix corresponding to the gene expression. Rownames should contain gene names/ids while samples should be in columns. |
train_influence |
Regulator influence scores of the train data set. |
minTarget |
The minimum number of targets for a regulator to be considered for actvity prediction when computing the influence. Default set to 10 |
experiment_influence |
Regulator influence scores for the condition of interest as a named vector with the TF as names. |
network |
CoRegNet object to be interrogated for building the linear models |
The predicted gene expression levels compute from the linear model and the experiment influence