PRANA: A Pseudo-Value Regression Approach for Differential Network Analysis of Co-Expression Data
The methodology work has been accepted to BMC Bioinformatics.
As of Spring 2023, the PRANA R package is available through CRAN: https://cran.r-project.org/web/packages/PRANA/index.html. The software paper has been submitted for consideration for publication in BMC Genomics.
This repository contains clinical and expression data, saved as combinedCOPD_RelatedGenesOnly.RDS. Of note, this looks at 28 COPD-related genes that were highlighted in a recent genome-wide association study (Sakornsakolpat et al., 2019). The full data is available from the Gene Expression Database with accession number GSE158699 (Wang et al., 2021).
- TotalConnectivity.R is to calculate the total connectivity of each gene.
- EmpiricalBayes_Datta_2005.R is to compute the adjusted p-values via empirical Bayes approach (Datta and Datta, 2005).
- PRANA_main.R is the primary code to analyze the data. This will load the first two codes, so please download all three R codes to apply our method. The code is heavily annotated for ease of implementation.
The user manual for PRANA is also provided in this repository, titled with PRANA_UserManual.pdf.
Sakornsakolpat, P., Prokopenko, D., Lamontagne, M., and et al. (2019). Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell- type and phenotype associations. Nature Genetics, 51(3), 494–505.
Wang, Z., Masoomi, A., Xu, Z., Boueiz, A., Lee, S., Zhao, T., Bowler, R., Cho, M., Silverman, E., Hersh, C., Dy, J., and Castaldi, P. (2021). Improved prediction of smoking status via isoform-aware RNA-seq deep learning models. PLoS Computational Biology, 17(10).
Datta, S. and Datta, S. (2005). Empirical Bayes screening of many p-values with applications to microarray studies. Bioinformatics, 21(9), 1987–1994.
If you encounter a bug or any suggestions to improve our work, please feel free to email me (Seungjun Ahn) at seungjun.ahn@mountsinai.org.