README.md

In ncats/MultiOmicsGraphPrediction: Network-Based Ensemble Prediction from IntLIM Predictors

Graph Ensemble Neural Network README

Code Structure

• The R directory includes all source code.
• The man directory includes compiled code.
• The inst directory contains a directory called extdata, which includes the following data sets:
• Simulated Data: A simulated data set with 54 training samples and 6 test samples, 6 entities of type 1, and 11 entities of type 2, where the outcome is a simulated continuous score.
• NCI-60 5-FU Data: A data with 46 training samples and 5 test samples, where each sample is a cell line, the first 1,000 of 17,987 gene entities, and 109 identified small molecule entities, where the outcome is IC50 response of the cell line to the 5-FU drug Tegafur.
• The vignettes directory includes sample files that illustrate how to run a typical workflow. These files are also run during package builds. We include a vignette for each of the data sets, i.e.:
• simDataVignette.Rmd
• nci60DataVignette.Rmd

Prerequisites

Code was developed and tested in R version 4.3.0. It is recommended that the user run this package with this or a later version of R.

GENN depends on the following R packages, all of which can be installed via CRAN: grDevices igraph IntLIM methods * stats

Installing and Using GENN

To install IntLIM, simply type the following in the R terminal:

install.packages("devtools")
library(devtools)
idevtools::install_github("ncats/GENN")

You may then load GENN to use in any R script by including the following command:

library("GENN")

Please see the vignettes for detailed examples using the GENN workflow.

Contact

If you encounter any problems running on the software, or find installation problems or bugs, please start an issue on the Issues tab or email XXX at [e-mail] or XXX at [e-mail]. We are also very open to any comments, including how we can improve and ameliorate the package.

ncats/MultiOmicsGraphPrediction documentation built on Aug. 23, 2023, 9:19 a.m.