A Powerful Suite for Volcano Mapping – EnhancedVolcano 1.18.0

Volcano plots are a presentation method commonly used to visualize the results of differential expression analysis, and are widely used in biology, genomics, drug development and other fields. With volcano maps, researchers can visualize differences in gene or molecule expression under different conditions and identify significant changes in biological processes, disease development, and more. Here to share with you a powerful and intuitive R suite for drawing volcano maps,Enhanced Volcano.

How to download the EnhancedVolcano kit?

# Download EnhancedVolcano package if (!requireNamespace('BiocManager', quietly = TRUE)) install.packages('BiocManager') BiocManager::install('EnhancedVolcano') # Check version packageVersion("EnhancedVolcano")

Perform RNA-seq result analysis

1. Load Kit and Load RNA-seq Results

Before using any R package, you need to firstuselibrary()to loadkit needed. RNA-seq files used in this examplecan be downloaded here.

# load package library(EnhancedVolcano) # load RNA-seq result RNAseq <- read.csv("C:/Users/USER/Desktop/RNAseq_Sample.csv", header = T) head(RNAseq)

After successfully inputting the RNA-seq results, you can directly draw the volcano map. The process is so simple and rude!

2. Draw the most basic volcano map

# draws the most basic volcano map EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name),x = 'Log.fold.change', y = 'P.value')

3. Modify logFC and P-value cutoffs, specify titles, adjust points, and label sizes

# Modify the logFC and P-value cut-off values, specify the size of the title, adjustment points and labels EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5)

4. Adjust the color and alpha value of dots

Variables that pass both the logFC and P-value thresholds are changed to red, and all others are colored black. In addition, the alpha value can control the transparency of the point:1 = 100% opaque;0 = 100% transparent.

# Adjust the color and alpha value of dots EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', title = 'control versus treatment', pCutoff = 10e -4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5, col=c('black', 'black', 'black', 'red3'), colAlpha = 1)

5. Adjust the punctuation shape

able to passshape()parameter specifies the punctuation shape. For more information on shape codes, please refer toggplot2:shape.

# Adjust punctuation shape EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5, shape = c(1, 4, 23, 25), colAlpha = 1)

6. Adjust legend position, size and text

# Adjust legend position, size and text EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', title = 'control versus treatment', pCutoff = 10e -4, FCcutoff = 1, cutoffLineType = 'twodash', cutoffLineWidth = 0.8,, pointSize = 3.0, labSize = 4.5, colAlpha = 1, legendLabels=c('Not sig.','Log (base 2) FC',' p-value', 'p-value & Log (base 2) FC'), legendPosition = 'right', legendLabSize = 16, legendIconSize = 5.0)

7. Add connectors to show more markers

# Add connector to show more markers EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', xlab = bquote(~Log[2]~ 'Log.fold.change'), title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5, legendIconSize = 3.0, drawConnectors = TRUE, widthConnectors = 0.5)

8. Only show certain tags

# only shows specific markers EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', selectLab = c('Hamp','Irx5','Myh7 ','Tecrl'), title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5)

9. Add a frame around the markup

# is framed outside the markerEnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', selectLab = c('Hamp','Irx5','Myh7 ','Tecrl'), title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5, labCol = 'black', labFace = 'bold', boxedLabels = TRUE, colAlpha = 4/5, legendLabSize = 14, legendIconSize = 4.0, drawConnectors = TRUE, widthConnectors = 1.0, colConnectors = 'black')

10. Flip the volcano map to the other side

# Flip the volcano map to other faces EnhancedVolcano(RNAseq,lab = as.character(RNAseq$Name), x = 'Log.fold.change', y = 'P.value', selectLab = c('Hamp','Irx5' ,'Myh7','Tecrl'), title = 'control versus treatment', pCutoff = 10e-4, FCcutoff = 1, pointSize = 3.0, labSize = 4.5, labCol = 'black', labFace = 'bold', boxedLabels = TRUE, colAlpha = 4/5, legendLabSize = 14, legendIconSize = 4.0, drawConnectors = TRUE, widthConnectors = 1.0, colConnectors = 'black') + coord_flip()

the above isEnhanced Volcano The most commonly used commands and parameters in the R suite, if you want to draw a more distinctive volcano map, you can refer toEnhanced Volcano Detailed instructions for the kit.

references

1. Blighe, K, S Rana, and M Lewis. Enhanced Volcano: Publication-ready volcano plots with enhanced coloring and labeling. 2018.

2. Enhanced Volcanoteaching website.