train_continuous_model: Train a linear model and predict the gene expression from an...

Description Usage Arguments Value

View source: R/CoregfluxFunctions.R

Description

Train a linear model and predict the gene expression from an experiment influence

Usage

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train_continuous_model(train_expression, train_influence, minTarget = 10,
  experiment_influence, network)

Arguments

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

Value

The predicted gene expression levels compute from the linear model and the experiment influence


CoRegFlux documentation built on Nov. 8, 2020, 5:21 p.m.