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Volcano Plot in R

Hi, I am trying to make volcano plot using EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling and my data looks like as below:

head(db_P7_db_veh)
Gene_symbol log2FoldChange   pvalue  DEG
Cmklr1      0.9830351 1.08e-06   UP
Akirin2     -0.6085560 1.28e-05 DOWN
Tgm2      1.2431722 1.35e-05   UP
Atp11a      0.7794673 1.47e-05   UP

The code I used is:

EnhancedVolcano(db_P7_db_veh,
            lab = rownames(db_P7_db_veh),
            x = 'log2FoldChange',
            y = 'pvalue' ,
            selectLab = c('Fmo3','Rab3b', 'Gata5', 'Acta2'))

My question is that the code is making the plot but I am trying to add the gene labels for some of the genes as shown in the code but it is not plotting with the gene names as I needed. There is no error message also. So, if anyone can help me in that then it would be highly appreciated. Thanks in advance!

r
• 2,437 views • link
updated by Kevin Blighe Kevin Blighe • written by sinha.puja • sinha.puja

1 answer

Hi,

It seems that you just need to use:

EnhancedVolcano(...,
  lab = db_P7_db_veh$Gene_symbol,
  ...)
• 0 views • link
written by Kevin Blighe Kevin Blighe

Thanks Kevin, it's working now. I have another question about maxoverlapconnectors when I am using maxoverlapsConnectors = Inf, my graph looks totally black with few spots of red and green because I get the following warning ggrepel: 1307 unlabeled data points (too many overlaps). Consider increasing max.overlaps

My code is below:

keyvals <- ifelse(
  db_P7_db_veh$log2FoldChange < -1.5 | db_P7_db_veh$pvalue < 0.05, 'green4',
  ifelse(db_P7_db_veh$log2FoldChange > 1.5 | db_P7_db_veh$pvalue < 0.05, 'red',
         'black'))
keyvals[is.na(keyvals)] <- 'black'
names(keyvals)[keyvals == 'red'] <- 'high'
names(keyvals)[keyvals == 'green4'] <- 'low'

EnhancedVolcano(db_P7_db_veh,
                lab = db_P7_db_veh$Gene_symbol,
                x = 'log2FoldChange',
                y = 'pvalue',
                selectLab = db_P7_db_veh$Gene_symbol[which(names(keyvals) %in% c('high', 'low'))],
                xlab = bquote(~Log[2]~ 'fold change'),
                pointSize = 2.5,
                labSize = 3.5,
                colCustom = keyvals,
                colAlpha = 0.5,
                legendPosition = 'right',
                legendLabSize = 15,
                legendIconSize = 5.0,
                drawConnectors = TRUE,
                widthConnectors = 1.0,
                colConnectors = 'black',
                arrowheads = FALSE,
                gridlines.major = TRUE,
                gridlines.minor = FALSE,
                border = 'partial',
                borderWidth = 1.5,
                borderColour = 'black',
                maxoverlapsConnectors = Inf)

Please help me in this. Thanks.

• 0 views • link
written by sinha.puja • sinha.puja

Yes, you may want to reduce the value of maxoverlapsConnectors, or, instead, increased the thresholds for statistical significance (pCutoff and FCcutoff) so that less genes are labelled

• 0 views • link
written by Kevin Blighe Kevin Blighe

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