6.0-Module6_Review_of_the_tools.Rmd

# Module 6: Review of the tools  

 *<font color="#827e9c">By Veronique Voisin, Chaitra Sarathy and Ruth Isserlin</font>*
 
## Final slides
[Lecture](./lectures/Pathways_2023_finalslides.pdf)  

  
## scRNA lab praticals

[scRNA-lab1_PBMC](#scRNA-lab1)

 - This lab starts from scRNA data from peripheral blood mononuclear cells. 

 - The cells from similar cell types were grouped into clusters. 

 - We extracted the gene lists corresponding to each cluster and run pathway analysis on it using g:Profiler. 

 - We also created pseudobulk from the data, ran GSEA and created an enrichment map.

[scRNAlab2_Glioblastoma](#scRNAlab2)

 - Similar to lab1, we extracted gene lists from scRNA clustering from glioblastoma data.

 - We created an mastermap by uploading in EnrichmentMap the pathway enrichment results for all the cluster gene lists.
  
[scNetViz](#scNetViz-lab)

 - scNetViz is a Cytoscape that download scRNA data from the SingleCellAtlas, calculated differential expression between clusters or defined catergories and create protein-protein interaction networks out of it.

##  Integrated assignment

[Integrated assignment](#integrated_assignment)

 - In this integrated assignment, all the tools viewed during the workshop from module 1 to module 5 are integrated. The dataset is a microarray dataset available publicly from GEO. 
 
## Integrated assignment bonus

[Automation](#ass_automation)

 - Experiment with automating your enrichment analysis pipeline using R.