index.Rmd

---
title: "Cytoscape Workflows"
output:
  html_document: default
  html_notebook: default
---

Collection of workflows as R Notebooks that use functionaility in R to process data as well as cyRest to communicate directly with Cytoscape.  Workflows start from raw data and result in cytoscape network outputs. 

## Enrichment Map Pipeline

Set of R notebooks to transform expression data to a ranked list and run them through Pathay enrichment pipeline. Pathway enrichment analysis helps gain mechanistic insight into large gene lists typically resulting from genome scale (–omics) experiments. It identifies biological pathways that are enriched in the gene list more than expected by chance. We explain pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists. The protocol is designed for biologists with no prior bioinformatics training and uses freely available software including g:Profiler, GSEA, Cytoscape and Enrichment Map.

```{r, echo=FALSE}
htmltools::img(src = knitr::image_uri("./EnrichmentMapPipeline/Figures/small_flowchart_EM.png"), 
               alt = 'logo', 
               style = 'margin:0px auto;display:block')
```


```{r, echo=FALSE}
htmltools::a(href="./EnrichmentMapPipeline/index.html","Enrichment Map Pipeline",
             style="margin:20px auto; text-align:center; display:block; font-size: 30px" )
              
```


## Cell Cell Interaction Workflow

Using a set of proteins designated as receptors, and ligands defined with a set of GO terms calculate the set of interactions that represent cell-cell interactions (for example Ligand-receptor, receptor-receptor, ...). This analysis is not limited to Cell-Cell interactions. You can define your own protein types, either manually or by choosing different go terms, and create your customized protein-protein interaction network.