PGCNA2 (Parsimonious Gene Correlation Network Analysis)
PGCNA is a gene correlation network analysis approach that is computationally simple yet yields stable and biologically meaningful modules and allows visualisation of very large networks, showing substructure and relationships that are normally hard to see. The parsimonious approach, retaining the 3 most correlated edges per gene, results in a vast reduction in network complexity meaning that large networks can be clustered quickly and reduced to a small output file that can be used by downstream software.
For more details see: Care, M.A., Westhead, D.R., Tooze, R.M., 2019. Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer. npj Syst. Biol. Appl. 5, 13. https://doi.org/10.1038/s41540-019-0090-7.
Please cite this when using PGCNA.
PGCNA paper website: http://pgcna.gets-it.net
PGCNA and PGCNA2
There are two versions of PGCNA:
- PGCNA, the original version of PGCNA (used in the original manuscript) : PGCNA.
- PGCNA2, a version of PGCNA that uses an improved community detection alogorithm: PGCNA2.
We highly recommend using PGCNA2.
Feedback and questions
If you have any queries or notice any bugs please email me at firstname.lastname@example.org (please include PGCNA in the subject heading).