---
title: "Volcano"
author: "Alex Emmons, Ph.D."
format:
  html:
    embed-resources: true
    code-fold: true
    code-tools: true
    code-overflow: wrap
toc: true
date: "January 17, 2024"
date-modified: last-modified
params: 
  data: "./deseq2_DEGs.csv"
---  

# Volcano Quarto Demonstration 


Here we will create a volcano plot from differential expression results. 

::: {.callout-tip}
Labels are ensembl IDs. For a more useful figure, add an annotation step.
:::
  
Learn more about Volcano plots [here](https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/rna-seq-viz-with-volcanoplot/tutorial.html){target=_blank}.  

## Create a Volcano Plot from DESeq2 differential expression results  

### Load the libraries
```{r}
#| message: false
library(EnhancedVolcano)
library(dplyr)
```


### Load the data from command line arguments  

The data were filtered to remove adjusted p-values that were NA; these were genes excluded by `DESeq2` as a part of independent filtering.  
```{r}

data<-read.csv(params$data,row.names=1) %>% filter(!is.na(padj))
```


### Plot 
  
Create label subsets for plotting.   

```{r}
labs<-head(row.names(data),5)

```


@fig-volcano_plot allows us to identify which genes are statistically significant with large fold changes.  
```{r}
#| label: fig-volcano_plot
#| fig-cap: "Enhanced Volcano Plot of bulk RNA-seq data from the package airway"
#| warning: false
EnhancedVolcano(data,
                title = "Enhanced Volcano with Airways",
                lab = rownames(data),
                selectLab=labs,
                labSize=3,
                drawConnectors = TRUE,
                x = 'log2FoldChange',
                y = 'padj')   

```


Other files in this working directory:   
```{bash}
ls
```