R package for quantiying pathway perturbations in gene co-expression networks between two timepoints.
- Preprocessing gene co-expression data.
- Compute gene co-expression networks defined as pathway specific biological processes obtained from KEGG and GO databases.
- Compute network rewiring scores and generate pathway specific summary statistics (as a pathway perturbation proxy).
# install.packages("devtools")devtools::install_github("kiakoudimi/NetworkRewiring")Pipeline overview:
- Prepare a gene expression data matrix (e.g. normalize, log2-transform)
- Construct an object describing the data, group and time points.
- Call
run_analysis()to estimate gene co-expression networks, gene rewiring, and pathway-specific statistical summaries over their gene rewiring members.
library(NetworkRewiring)
net<- new("gene_network",
gene_intensities=gi,
group_name='Healthy',
timepoints= c(1,2),
metadata=ids,
output_dir='results',
dataset='Dataset_name',
database='KEGG',
pathways=pathways,
group_col="Group",
subjects_ids="id",
sample_ids="ID",
time_col="Day",
time_labels= c('Day1', 'Day2'))
run_analysis(net)The examples/scripts/ folder includes three scripts as:
| Script | Usage |
|---|---|
run_example.R | Code for reproducing the pipeline on the datasets GSE54514, GSE48080, and GSE95233. Their data are in examples/data/ folder. |
run_template.R | Template code for running the pipeline on different datasets. |
run_example_visualization.R | Code for reproducing figures and visualize results on the example datasets. |
gene_intensities- a numeric matrix with gene as rows and sample IDs as columnsmetadata- a data.frame with one row per sample that includes a group columns (e.g. 'Group'), a time point column (e.g. 'Day'), a subject column (e.g. 'id'), and a sample ID column (e.g. 'ID').pathways- a data.frame of pathways or biological processes (see examples for KEGG and GO in folderdata/).
Estimated edge lists, rewiring scores and statistical summaries will be exported in:
<output_dir>/<dataset>/<database>/<group_name><timepoint1><timepoint2>
inlcuding the folders edge_lists, dynet_score, and an .RData file with statistical summary.
CC BY-NC 4.0 License