predict_immune_response: Immune response prediction

In olapuentesantana/easier_manuscript: Evaluate patient immune response to ICBs through a systems approach

Description

predict_immune_response predicts immune response using two algorithms: multi-task elastic net and bayesian efficient multi-kernel algorithm. While BEMKL can exploit information across different input and output datasets, multi-task elastic net can only do so for response variables. Another advantage of BEMKL is missing data handling, which is not the case for the other algorithm.

Usage

predict_immune_response(
  pathways = NULL,
  immunecells = NULL,
  tfs = NULL,
  lrpairs = NULL,
  ccpairs = NULL,
  cancertype
)

Arguments

pathways	numeric matrix with data
immunecells	numeric matrix with data
tfs	numeric matrix with data
lrpairs	numeric matrix with data
ccpairs	numeric matrix with data
cancertype	string character

Details

These algorithms use model parameters learned during training on different types of data in order to compute the immune response.

Value

Predictions for each model building.

olapuentesantana/easier_manuscript documentation built on Sept. 22, 2021, 9:42 p.m.