V2.2.0

PyWGCNA V2.2

Compatible with the new version of Numpy (>2.1.0)
Compatible with the new version of pandas (>2.0.0)
Compatible with the new version of matplotlib (>3.9.0)
Update module_trait_relationships_heatmap()
Update all Tutorials to be compatible with this version

V2.1.3

PyWGCNA V2.1.0

• Compatible with the new version of pandas (>2.0.0)
• Compatible with the new version of matplotlib (>3.9.0)
• Update module_trait_relationships_heatmap()
• Update all Tutorials to be compatible with this version

P.S: LAST UPDATE OCT 2024

V1.20.4

PyWGCNA V1.20

• Fix minor issues
• Add options for calculating module-trait relationship
• Remove similar colors with different spells
• Add a new method for comparing multiple networks at once
• Add function to find top n hub genes in each module
• Improve visualizations
• Improved compatibility with current and future NumPy, SciPy, and pandas.

v1.15.0

PyWGCNA V1.8.0

Add more post-analysis options:

• do functional enrichment analysis including Go, KEGG and REACTOME
• recover gene-gene interaction using STRING database
• More option to visualize modules

add more tutorials to understand several functionality of package

v1.0.1

First public release!
Features include:

1. Finding clusters (modules) of highly correlated genes
2. Ploting module eigengene for relating modules to one another and to external sample traits (using eigengene network methodology)
3. Calculating module membership measures
4. Comparing PyWGCNA to another PyWGCNA/single cell gene markers

V0.6

finding modules based on expression data and analysed the results

v0.2-alpha

internal use add more feature to comparing part