Tutorials
=========

-  `Data input, cleaning and pre-processing <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/Data_format.md>`_: How to format, clean and preprocess your input data for PyWGCNA
-  `Quick Start <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/Quick_Start.ipynb>`_: How to load data into PyWGCNA, find modules, and analyze them
-  `PyWGCNA object <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/PyWGCNA_object.ipynb>`_: How to interact with PyWGCNA objects and some parameters we have them in the object and how you can access them
-  `Compare two PyWGCNA objects <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/Comparison_two_PyWGCNAs.ipynb>`_: How to compare two PyWGCNA objects
-  `Compare more than two PyWGCNA objects <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/Comparison_multi_PyWGCNAs.ipynb>`_: How to compare three PyWGCNA objects
-  `Compare PyWGCNA objects to gene marker list <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/Comparison_PyWGCNA_geneMarker.ipynb>`_: How to compare PyWGCNA objects to external gene lists (here shown on marker genes from single-cell data)
-  `Functional enrichment analysis  <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/functional_enrichment_analysis.ipynb>`_: How to perform functional enrichment analysis using databases such as GO, KEGG, and REACTOME in PyWGCNA object
-  `Visualize modules as network <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/network_analysis.ipynb>`_: How to visualize PyWGCNA objects as a network
-  `Recover Protein-Protein Interaction <https://github.com/mortazavilab/PyWGCNA/tree/main/tutorials/protein_protein_interaction.ipynb>`_: How to find and plot PPI using STRING database.