Topyfic v0.4.18

Topyfic v0.4.0

• Add M-A plot to compare two topics based on their gene weights and calculate the modified z-score
• Compare two topics based on their gene weights
• Embedded other models to be able to use downstream analysis
• Add different statistical comparisons to compare topics i.e. Jensen–Shannon divergence
• Save train and topModel objects as a h5 file to be able to read and work it without using Python
• update topic_trait_relationships_heatmap()

Topyfic >= v0.4.17

• due to changes in random.shuffle(), any version >= 0.4.17 only compatible with python >= 3.9
• update structure_plot() to be faster

V0.2.2

Topyfic V0.2.2

• Adding more options to tune the parameters you used to learn LDA models
• Adding options to combine multiple trains which help you to save time

V0.1.10

Topyfic is a Python package designed to identify reproducible latent Dirichlet allocation (LDA) using Leiden clustering and harmony for single-cell epigenomics data

Topyfic has a lot of options for downstream analysis

• GSEA
• GO/KEGG
• REACTOME
• Structure plots
• Pie chart
• Comparison across topics within/across multiple runs
• and lots of other visualization options

v0.0.5-alpha

Topyfic is a Python package designed to identify reproducible latent Dirichlet allocation (LDA) using Leiden clustering and harmony for single-cell epigenomics data