Download gene expression data from GRAND for the following data sets, saving all to the same directory:
You will need to install the GitHub version of netZooR to run UNAGI. Follow the instructions to install netZooR.
Run GenerateCoexpression.R, changing the following variables in the script prior to running:
expressionDir: Directory where expression data are storedcoexpressionDir: Directory where you wish to store coexpression data
Run RunUNAGI.R, changing the following variables in the script prior to running. This script generates Supplementary Tables 1-5 as well as filtered coexpression data.
coexpressionDir: Directory where coexpression data are storedfilteredCoexpressionDir: Directory where you wish to store the filtered coexpressionunagiDir: Directory where you wish to store UNAGI results
Run generate_rand_sets.R, changing the following variables in the script prior to running:
filteredCoexpressionDir: Directory where the filtered coexpression is storedrandomSetDir: Directory where you wish to store the random gene sets
We run UNAGI on randomized gene sets to compare the connectivity between actual genes of interest to connectivity between random genes. To do this, run unagi_serial_rand_runs.R, changing the following variables in the script prior to running:
coexpressionDir: Directory where coexpression data are storedrandomSetDir: Directory where the random gene sets are storedrandResultDir: Directory where the UNAGI results on random gene sets should be stored
To plot the networks in Figure 1 and Supplementary Figure 1 and to obtain the results in Tables 1 and 2, run UNAGI_GRAND_analysis.R, changing the following variables in the script prior to running:
unagiDir: Directory where UNAGI results are storedrandResultDir: Directory where the UNAGI results on random gene sets are storedtableDir: Directory where result tables should be storedplotDir:Directory where network plots should be stored