2.2 years ago by

Kevin Blighe ♦ 53k wrote:

Edit (October 24, 2018):

This is now a Bioconductor package: EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling

---------------------------------------------

Your code appears to run fine on my DESeq2 results objects:

I normally do these simple volcano plots a different way:

par(mar=c(5,5,5,5), cex=1.0, cex.main=1.4, cex.axis=1.4, cex.lab=1.4)

topT <- as.data.frame(resultsObject)

#Adjusted P values (FDR Q values)
with(topT, plot(log2FoldChange, -log10(padj), pch=20, main="Volcano plot", cex=1.0, xlab=bquote(~Log[2]~fold~change), ylab=bquote(~-log[10]~Q~value)))

with(subset(topT, padj<0.05 & abs(log2FoldChange)>2), points(log2FoldChange, -log10(padj), pch=20, col="red", cex=0.5))

#with(subset(topT, padj<0.05 & abs(log2FoldChange)>2), text(log2FoldChange, -log10(padj), labels=subset(rownames(topT), topT$padj<0.05 & abs(topT$log2FoldChange)>2), cex=0.8, pos=3))

#Add lines for absolute FC>2 and P-value cut-off at FDR Q<0.05
abline(v=0, col="black", lty=3, lwd=1.0)
abline(v=-2, col="black", lty=4, lwd=2.0)
abline(v=2, col="black", lty=4, lwd=2.0)
abline(h=-log10(max(topT$pvalue[topT$padj<0.05], na.rm=TRUE)), col="black", lty=4, lwd=2.0)

There is an even better solution that I and colleagues developed using ggplot2, which allows you to easily fit labels into your plot using ggrepel().

ADD COMMENT • link modified 15 months ago • written 2.2 years ago by Kevin Blighe ♦ 53k

@Kevin wow the author himself ...yes i took the code from this site code

ADD REPLY • link written 2.2 years ago by krushnach80 • 630

Glad to have helped. Note the particular use of the bquote() function in order to get super- and sub-script. These are small modifications but can make a plot feel more professional. bquote() also works with ggplot2 (here I've used it with base functions).

ADD REPLY • link written 2.2 years ago by Kevin Blighe ♦ 53k

@Kevin i have some issues Im not able to get the following with the code which you have given as im trying to include

so this is my condition

Up-regulated: =/> 0.58 (Green color)
Down-regulated: =/> -0.59 (Red color)
Significant: =/>1.3 (-Log10 p-Value)

its like all the data points are getting overlapped with same color no distinction

ADD REPLY • link written 24 months ago by krushnach80 • 630

Can you paste your code so that I can put this in context?

ADD REPLY • link written 24 months ago by Kevin Blighe ♦ 53k

okay here is the code im using

par(mar=c(5,5,5,5), cex=1.0, cex.main=1.4, cex.axis=1.4, cex.lab=1.4)
res <- read.csv("volcano.txt", header=TRUE,sep = '\t')

topT <- as.data.frame(res)
head(topT)

with(topT, plot(lfc, -log10(padj), pch=20, main="Volcano plot", cex=1.0, xlab=bquote(~Log[2]~fold~change), ylab=bquote(~-log[10]~P~value)))

with(subset(topT, padj<0.05 & abs(lfc)>=0.58), points(lfc, -log10(padj), pch=20, col="red", cex=0.5))

with(subset(topT, padj<0.05 & abs(lfc)>=-0.59), points(lfc, -log10(padj), pch=20, col="green", cex=0.5))

ADD REPLY • link written 24 months ago by krushnach80 • 630

Yes, the last two lines contradict each other, specifically padj<0.05 & abs(lfc)>=0.58) and padj<0.05 & abs(lfc)>=-0.59).

I think that you want to colour positive fold-change genes as red, and negative as green? Try this:

par(mar=c(5,5,5,5), cex=1.0, cex.main=1.4, cex.axis=1.4, cex.lab=1.4)
res <- read.csv("volcano.txt", header=TRUE,sep = '\t')
topT <- as.data.frame(res)
head(topT)
with(topT, plot(lfc, -log10(padj), pch=20, main="Volcano plot", cex=1.0, xlab=bquote(~Log[2]~fold~change), ylab=bquote(~-log[10]~P~value)))
with(subset(topT, padj<0.05 & lfc>=0.58), points(lfc, -log10(padj), pch=20, col="red", cex=0.5))
with(subset(topT, padj<0.05 & lfc<=-0.59), points(lfc, -log10(padj), pch=20, col="green", cex=0.5))

ADD REPLY • link modified 24 months ago • written 24 months ago by Kevin Blighe ♦ 53k

"I think that you want to colour positive fold-change genes as red, and negative as green? Try this:" yes thats what i need to show

ADD REPLY • link written 24 months ago by krushnach80 • 630

Yep, take a look at the code that I pasted (above). You just needed to remove the abs() function call, and switch the 'greater than' sign to a 'less than' sign on the last line

ADD REPLY • link modified 24 months ago • written 24 months ago by Kevin Blighe ♦ 53k

Hi Kevin,

I am wondering if you have rscript showing the upreguted and down regulated? Can you share them?

ADD REPLY • link written 19 months ago by bioinfool • 20

Yes, please take a look here: https://github.com/kevinblighe/EnhancedVolcano

In which program did you conduct differential expression?

ADD REPLY • link written 19 months ago by Kevin Blighe ♦ 53k

Thanks for the quick reply.

I used edgeR in getting my DE. Once I got them, I pre-filtered my DE list in excel. I only extract FDR<1e-5 which is my significant. Then from those list, my up-reg is log2FC>0 while my down is log2FC<0. I wanted to plot my FDR against log2FC.

Can you embed the script here? Thank you very much!

ADD REPLY • link written 19 months ago by bioinfool • 20

Here is the code for data in an EdgeR results table:

EnhancedVolcanoEdgeR <- function(toptable, NominalCutoff, AdjustedCutoff, LabellingCutoff, FCCutoff, main)
{
    toptable$Significance <- "NS"
    toptable$Significance[(abs(toptable$logFC) > FCCutoff)] <- "FC"
    toptable$Significance[(toptable$FDR<AdjustedCutoff)] <- "FDR"
    toptable$Significance[(toptable$FDR<AdjustedCutoff) & (abs(toptable$logFC)>FCCutoff)] <- "FC_FDR"
    table(toptable$Significance)
    toptable$Significance <- factor(toptable$Significance, levels=c("NS", "FC", "FDR", "FC_FDR"))

    plot <- ggplot(toptable, aes(x=logFC, y=-log10(FDR))) +

        #Add points:
        #   Colour based on factors set a few lines up
        #   'alpha' provides gradual shading of colour
        #   Set size of points
        geom_point(aes(color=factor(Significance)), alpha=1/2, size=0.8) +

        #Choose which colours to use; otherwise, ggplot2 choose automatically (order depends on how factors are ordered in toptable$Significance)
        scale_color_manual(values=c(NS="grey30", FC="forestgreen", FDR="royalblue", FC_FDR="red2"), labels=c(NS="NS", FC=paste("LogFC>|", FCCutoff, "|", sep=""), FDR=paste("FDR Q<", AdjustedCutoff, sep=""), FC_FDR=paste("FDR Q<", AdjustedCutoff, " & LogFC>|", FCCutoff, "|", sep=""))) +

        #Set the size of the plotting window
        theme_bw(base_size=24) +

        #Modify various aspects of the plot text and legend
        theme(legend.background=element_rect(),
            plot.title=element_text(angle=0, size=12, face="bold", vjust=1),

            panel.grid.major=element_blank(),   #Remove gridlines
            panel.grid.minor=element_blank(),   #Remove gridlines

            axis.text.x=element_text(angle=0, size=12, vjust=1),
            axis.text.y=element_text(angle=0, size=12, vjust=1),
            axis.title=element_text(size=12),

            #Legend
            legend.position="top",          #Moves the legend to the top of the plot
            legend.key=element_blank(),     #removes the border
            legend.key.size=unit(0.5, "cm"),    #Sets overall area/size of the legend
            legend.text=element_text(size=8),   #Text size
            title=element_text(size=8),     #Title text size
            legend.title=element_blank()) +     #Remove the title

        #Change the size of the icons/symbols in the legend
        guides(colour = guide_legend(override.aes=list(size=2.5))) +

        #Set x- and y-axes labels
        xlab(bquote(~Log[2]~ "fold change")) +
        ylab(bquote(~-Log[10]~adjusted~italic(P))) +

        #Set the axis limits
        #xlim(-6.5, 6.5) +
        #ylim(0, 100) +

        #Set title
        ggtitle(main) +

        #Tidy the text labels for a subset of genes
        geom_text(data=subset(toptable, FDR<LabellingCutoff & abs(logFC)>FCCutoff),
            aes(label=rownames(subset(toptable, FDR<LabellingCutoff & abs(logFC)>FCCutoff))),
            size=2.25,
            #segment.color="black", #This and the next parameter spread out the labels and join them to their points by a line
            #segment.size=0.01,
            check_overlap=TRUE,
            vjust=1.0) +

        #Add a vertical line for fold change cut-offs
        geom_vline(xintercept=c(-FCCutoff, FCCutoff), linetype="longdash", colour="black", size=0.4) +

        #Add a horizontal line for P-value cut-off
        geom_hline(yintercept=-log10(AdjustedCutoff), linetype="longdash", colour="black", size=0.4)

    return(plot)
}

Requires

ggplot2

Execution

EnhancedVolcanoDESeq2(topTable, NominalCutoff, AdjustedCutoff, LabellingCutoff, FCCutoff, main)
EnhancedVolcanoEdgeR(topTable, NominalCutoff, AdjustedCutoff, LabellingCutoff, FCCutoff, main)

Example

EnhancedVolcanoDESeq2(topTable=results, AdjustedCutoff=0.05, LabellingCutoff0.05, FCCutoff=2.0, main="DESeq2 results")
EnhancedVolcanoEdgeR(topTable=results, AdjustedCutoff=0.05, LabellingCutoff0.05, FCCutoff=2.0, main="EdgeR results")

Parameters

toptable, data-frame of test statistics. Requires at least the following
gene names as rownames
column named 'log2FoldChange' for DESeq2 or 'logFC' for EdgeR
column named 'padj' for DESeq2 or 'FDR' for EdgeR
NominalCutoff, nominal p-value cut-off for statistical significance (obsolete)
AdjustedCutoff, adjusted p-value cut-off for statistical significance
LabellingCutoff, adjusted p-value cut-off for statistical significance for labels
FCCutoff, absolute log (base 2) fold change cut-off for statistical significance
main, title

ADD REPLY • link written 19 months ago by Kevin Blighe ♦ 53k

@Kevin

I have this data not row data to do DESeq2 myself

Gene Name   q value A+B: OAC vs normal Log2FC   Minus log10 (q-value) 
PRDM1   0.000113142 -1.18   3.95
TRABD   0.000688272 0.61    3.16
WWC3    0.038536606 -0.46   1.41
LYNX1   0.022322605 -1.54   1.65
ALOX15B 3.97666E-06 -2.02   5.40
RAP2C   0.030696226 -0.35   1.51
FBP2    0.001542994 1.80    2.81
GBP6    1.44846E-08 -2.54   7.84

I don't know how to feed this into your tutorial for volcano plot instead of a top table you have from DESeq2

Can you help me please?

Thank you

ADD REPLY • link written 4 months ago by A • 3.7k

Hey, you seem to have all columns that you need

EnhancedVolcano(res1,
    lab = df[,'Gene Name'],
    x = 'Log2FC',
    y = 'q value A+B: OAC vs normal')

Using Q values is not the typical approach for volcanos, but it is no major issue.

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Thanks a lot worked well

Sorry @Kevin I am wondering if I want to put a horizontal line for the threshold used for the q-value (0.05) and two vertical lines (0.6 and -0.6 log2 fold change) for the thresholds used for fold change. The points that represent proteins with q<0.05 and log2FC>0.6 (up-regulated proteins) be red whereas the points with q<0.05 and log2FC<-0.6t (down-regulated proteins) be blue. In your tutorial I am seeing vertical line but how would be with horizontal line?

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

Oh, sure, you can add any number of lines with the following parameters:

EnhancedVolcano(
  ...
  hline = c(10e-12, 10e-36, 10e-60, 10e-84),
  hlineCol = c('grey0', 'grey25','grey50','grey75'),
  hlineType = 'longdash',
  hlineWidth = 0.8,
  ...)

For vertical lines, they are:

vline
vlineCol
vlineType
vlineWidth

You can add any number of lines.

Then, there are also the main cut-off lines:

cutoffLineType
cutoffLineCol
cutoffLineWidth

...and the standard ggplot2 engine lines:

gridlines.major = FALSE
gridlines.minor = FALSE

[source: https://github.com/kevinblighe/EnhancedVolcano#adjust-cut-off-lines-and-add-extra-threshold-lines]

ADD REPLY • link modified 4 months ago • written 4 months ago by Kevin Blighe ♦ 53k

Sorry Kevin

With

> EnhancedVolcano(volcano,
+                 lab = volcano[,'Gene.Name'],
+                 x = 'A.B..OAC.vs.normal.Log2FC',
+                 y = 'q.value',
+                 xlim = c(-8, 8),
+                 title = 'Normal oesophagus versus Tumour',
+                 pCutoff = 0.05,
+                 FCcutoff = 0.6,
+                 transcriptPointSize = 1.5,
+                 transcriptLabSize = 3.0,    col=c('blue', 'blue', 'blue', 'red3'),
+                 colAlpha = 1,    cutoffLineType = 'blank',
+                 cutoffLineCol = 'black',
+                 cutoffLineWidth = 0.8,
+                 hline = c(10e-12, 10e-36, 10e-60, 10e-84),
+                 hlineCol = c('grey0', 'grey25','grey50','grey75'),
+                 hlineType = 'longdash',
+                 hlineWidth = 0.8,
+                 gridlines.major = FALSE,
+                 gridlines.minor = FALSE)
Warning message:
Removed 3 rows containing missing values (geom_hline). 
>

I finished with

enter image description here

But this is far from what I need to put a horizontal line for q-value < 0.05 and two vertical lines for 0.6 and -0.6 log2 fold change

I don't know how to do that can you help please?

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

Hey F, as you are plotting Q values, you will have to change the y-axis label by adding: ylab = bquote(~-Log[10] ~ italic(Q))

Also, the cut-off lines are not appearing because you have cutoffLineType = 'blank'

Take a look (using a different dataset)

cutoffLineType = 'blank'

EnhancedVolcano(volcano,
  lab = volcano[,'Gene.Name'],
  x = 'A.B..OAC.vs.normal.Log2FC',
  y = 'q.value',
  ylab = bquote(~-Log[10] ~ italic(Q)),
  xlim = c(-8, 8),
  title = 'Normal oesophagus versus Tumour',
  pCutoff = 0.05,
  FCcutoff = 0.6,
  transcriptPointSize = 1.5,
  transcriptLabSize = 3.0,    col=c('blue', 'blue', 'blue', 'red3'),
  colAlpha = 1,
  cutoffLineType = 'blank',
  cutoffLineCol = 'black',
  cutoffLineWidth = 0.8,
  hline = c(10e-12, 10e-36, 10e-60, 10e-84),
  hlineCol = c('grey0', 'grey25','grey50','grey75'),
  hlineType = 'longdash',
  hlineWidth = 0.8,
  gridlines.major = FALSE,
  gridlines.minor = FALSE)

cutoffLineType = 'solid'

EnhancedVolcano(volcano,
  lab = volcano[,'Gene.Name'],
  x = 'A.B..OAC.vs.normal.Log2FC',
  y = 'q.value',
  ylab = bquote(~-Log[10] ~ italic(Q)),
  xlim = c(-8, 8),
  title = 'Normal oesophagus versus Tumour',
  pCutoff = 0.05,
  FCcutoff = 0.6,
  transcriptPointSize = 1.5,
  transcriptLabSize = 3.0,    col=c('blue', 'blue', 'blue', 'red3'),
  colAlpha = 1,
  cutoffLineType = 'solid',
  cutoffLineCol = 'black',
  cutoffLineWidth = 0.8,
  hline = c(10e-12, 10e-36, 10e-60, 10e-84),
  hlineCol = c('grey0', 'grey25','grey50','grey75'),
  hlineType = 'longdash',
  hlineWidth = 0.8,
  gridlines.major = FALSE,
  gridlines.minor = FALSE)

Another issue in your code is that the values passed to hline are too low. You could try hline = c(0.10, 0.15, 0.2, 0.25), i.e., in this case, extra cut-offs for Q-values 0.1, 0.15, 0.2, and 0.25

To avail of most recent functionality, you should also install the current dev version:

devtools::install_github('kevinblighe/EnhancedVolcano')

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Thank you so much

I finished with this

enter image description here

Again vertical line is far from and also plot seems a bit crowded that would be nice to show a list of genes instead of all

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

There are a few ways to further manage the gene labels:

use drawConnectors = TRUE
use selectLab = c('TGM1', 'EPCAM', 'CLDN3')
increase labSize to, e.g., labSize = 5.0

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Sorry Kevin I want

For the non-significant (NS)  light grey 
For the Log2FC  darker grey
For the -Log10Q  darker grey
For the -Log10Q & Log2FC>0  red
For the -Log10Q & Log2FC<0 blue

But this

> EnhancedVolcano(res2,
+                 lab = rownames(res2),
+                 x = 'log2FoldChange',
+                 y = 'pvalue',
+                 xlim = c(-8, 8),
+                 title = 'Tumour versus Normal oesophagus',
+                 pCutoff = 0.05,
+                 FCcutoff = 0.6,col=c('grey75', 'grey50', 'grey25', 'red','blue'),
+                 colAlpha = 1)
>

Gives this enter image description here How I can get blue in left side and red in right side while here I am getting red in both side

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

i see. In the default colour scheme, there can only be 4 colours. If you need to use 5 colours, you will have to customise it. There is more information here: https://github.com/kevinblighe/EnhancedVolcano#over-ride-colouring-scheme-with-custom-key-value-pairs

Do you think that you can follow that?

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Thank you so much

I did like below but after running R never finished with that I think I am doing something wrong

keyvals <- rep('black', nrow(res2))
 names(keyvals) <- rep('Mid', nrow(res2))
 keyvals[which(res2$log2FoldChange > 0.6 & res2$pvalue < 0.05)] <- 'red'
 names(keyvals)[which(res2$log2FoldChange > 0.6 & res2$pvalue < 0.05)] <- 'high'
 keyvals[which(res2$log2FoldChange < -0.6 & res2$pvalue < 0.05)] <- 'blue'
 names(keyvals)[which(res2$log2FoldChange < -0.6 & res2$pvalue < 0.05)] <- 'low'
 unique(names(keyvals))
[1] "low"  "high" "Mid" 
 unique(keyvals)
[1] "blue"  "red"   "black"
 keyvals[which(abs(res2$log2FoldChange) < 0.6 & res2$pvalue  0.05)] <- 'grey75'
 names(keyvals)[which(abs(res2$log2FoldChange) < 0.6 & res2$pvalue  0.05)] <- 'NS'
 unique(keyvals)
[1] "blue"   "red"    "black"  "grey75"
 keyvals[which(abs(res2$log2FoldChange) > 0.6 & res2$pvalue  0.05)] <- 'grey50'
 names(keyvals)[which(abs(res2$log2FoldChange) > 0.6 & res2$pvalue  0.05)] <- 'log2FoldChange'
 keyvals[which(abs(res2$log2FoldChange) < 0.6 & res2$pvalue < 0.05)] <- 'grey25'
 names(keyvals)[which(abs(res2$log2FoldChange)  < 0.6 & res2$pvalue < 0.05)] <- '-Log10Q'
 unique(keyvals)
[1] "blue"   "red"    "grey25" "grey75" "grey50" "black" 
 unique(names(keyvals))
[1] "low"            "high"           "-Log10Q"       
[4] "NS"             "log2FoldChange" "Mid"           
 EnhancedVolcano(res2,
                                   lab = rownames(res2),
                                   x = 'log2FoldChange',
                                   y = 'pvalue',
                                   selectLab = rownames(res2)[which(names(keyvals) %in% c('NS','log2FoldChange','-Log10Q','low','high'))],
                                   xlim = c(-6.5,6.5),
                                   xlab = bquote(~Log[2]~ 'fold change'),
                                   title = 'Custom colour over-ride',
                                   pCutoff = 0.05,
                                   FCcutoff = 0.6,
                                   colCustom = keyvals,
                                   colAlpha = 1,
                                   legendPosition = 'right',
                                   legendLabSize = 15,
                                   legendIconSize = 5.0,
                                   drawConnectors = TRUE,
                                   widthConnectors = 0.5,
                                   colConnectors = 'grey50',
                                   gridlines.major = TRUE,
                                   gridlines.minor = FALSE,
                                   border = 'partial',
                                   borderWidth = 1.5,
                                   borderColour = 'black')

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

Hey, here is a reproducible example using the data mentioned on the vignette.

Remember, and assuming that you are using the same data as before, you need to change the ylab parameter to ylab = bquote(~-Log[10] ~ italic(Q)), as you are plotting q-values (adjusted p-values). Also, when deriving the key-value pairs, you need to specify the correct columns, so, for example:

keyvals[which(abs(res2$A.B..OAC.vs.normal.Log2FC) > FC & res2$q.value > p)] <- 'grey50'
names(keyvals)[which(abs(res2$A.B..OAC.vs.normal.Log2FC) > FC & res2$q.value > p)] <- 'log2FoldChange'

Please adapt (modify) the code to suit your data.

library(EnhancedVolcano)
library(airway)
library(magrittr)
data('airway')
airway$dex %<>% relevel('untrt')

library('DESeq2')
dds <- DESeqDataSet(airway, design = ~ cell + dex)
dds <- DESeq(dds, betaPrior=FALSE)
res2 <- results(dds,
  contrast = c('cell', 'N061011', 'N61311'))
res2 <- lfcShrink(dds,
  contrast = c('cell', 'N061011', 'N61311'), res=res2)


FC <- 0.6
p <- 10e-3

keyvals <- rep('grey75', nrow(res2))
names(keyvals) <- rep('NS', nrow(res2))

keyvals[which(abs(res2$log2FoldChange) > FC & res2$pvalue > p)] <- 'grey50'
names(keyvals)[which(abs(res2$log2FoldChange) > FC & res2$pvalue > p)] <- 'log2FoldChange'

keyvals[which(abs(res2$log2FoldChange) < FC & res2$pvalue < p)] <- 'grey25'
names(keyvals)[which(abs(res2$log2FoldChange)  < FC & res2$pvalue < p)] <- '-Log10Q'

keyvals[which(res2$log2FoldChange < -FC & res2$pvalue < p)] <- 'blue2'
names(keyvals)[which(res2$log2FoldChange  < -FC & res2$pvalue < p)] <- 'Signif. down-regulated'

keyvals[which(res2$log2FoldChange > FC & res2$pvalue < p)] <- 'red2'
names(keyvals)[which(res2$log2FoldChange > FC & res2$pvalue < p)] <- 'Signif. up-regulated'

unique(keyvals)
unique(names(keyvals))

EnhancedVolcano(res2,
  lab = rownames(res2),
  x = 'log2FoldChange',
  y = 'pvalue',
  #selectLab = rownames(res2)[which(names(keyvals) %in% c('NS','log2FoldChange','-Log10Q','low','high'))],
  xlim = c(-6.5,6.5),
  xlab = bquote(~Log[2]~ 'fold change'),
  ylab = bquote(~-Log[10] ~ italic(P)),
  title = 'Custom colour over-ride',
  pCutoff = 10e-3,
  FCcutoff = 0.6,
  pointSize = 2.5,
  labSize = 4.5,
  #shape = c(6, 4, 2, 11, 15),
  colCustom = keyvals,
  colAlpha = 0.75,
  legendPosition = 'right',
  legendLabSize = 15,
  legendIconSize = 5.0,
  drawConnectors = FALSE,
  widthConnectors = 0.5,
  colConnectors = 'grey50',
  gridlines.major = TRUE,
  gridlines.minor = FALSE,
  border = 'partial',
  borderWidth = 1.5,
  borderColour = 'black')

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Thank you so much to be this much helpful

I used

  > EnhancedVolcano(res2,
+                 lab = rownames(res2),
+                 x = 'log2FoldChange',
+                 y = 'pvalue',
+                 selectLab = c('DSG2','CALML4','MLEC','PKP2','VIL1','EPCAM','KRT8','FUT8','MUC13','TSPAN8','TBXAS1','GBP6','CLIC3','TACC2','TGM1','CRABP2','MAST4','FASN','ALDH3A1','ACPP','ANXA8L2'),
+                 xlim = c(-6.5,6.5),
+                 xlab = bquote(~Log[2]~ 'fold change'),
+                 ylab = bquote(~-Log[10] ~ italic(Q)),
+                 title = 'Tumour versus normal oesophagus',
+                 pCutoff = 0.05,
+                 FCcutoff = 0.6,
+                 #shape = c(6, 4, 2, 11, 15),
+                 colCustom = keyvals,
+                 colAlpha = 4/5,
+                 legend=c('NS','Log (base 2) fold-change','P value',
+                          'P value & Log (base 2) fold-change'),
+                 legendPosition = 'right',
+                 legendLabSize = 20,
+                 legendIconSize = 10,
+                 drawConnectors = TRUE,
+                 widthConnectors = 1.2,
+                 colConnectors = 'black',boxedLabels=TRUE,labSize =10)

Worked well, but when I want a box around the genes I got error

enter image description here

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

boxedLabels was only added in a recent version. You can update to the very latest version with:

devtools::install_github('kevinblighe/EnhancedVolcano')

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Sorry I updated that right now but the same error

Error in EnhancedVolcano(res2, lab = rownames(res2), x = "log2FoldChange",  : 
  unused arguments (labFace = "bold", boxedLabels = TRUE)

Also today I am getting error about labSize argument too

Error in EnhancedVolcano(res2, lab = rownames(res2), x = "log2FoldChange",  : 
  unused arguments (pointSize = 3, labSize = 3)

Is this because of colCustom = keyvals?

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

I am sorry, but you are therefore not using the latest version. I have just confirmed on my computer that boxedLabels and labSize are functioning correctly.

Please restart your R session, install the development version of EnhancedVolcano, and then confirm (via sessionInfo()) that you are using v1.3.4

Please do not post again until you debug these problems some more.

Thank you! :)

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Sorry you were right, problem was the update

Sorry to be too silly

ADD REPLY • link written 4 months ago by A • 3.7k

No problem, Angel.

ADD REPLY • link written 4 months ago by Kevin Blighe ♦ 53k

Sorry Kevin

By these lines I plotted the volcano

FC <-0.5
p <- 0.05
keyvals <- rep('grey75', nrow(res_responders))
names(keyvals) <- rep('NS', nrow(res_responders))
keyvals[which(abs(res_responders$log2FoldChange) > FC & res_responders$pvalue > p)] <- 'grey50'
names(keyvals)[which(abs(res_responders$log2FoldChange) > FC & res_responders$pvalue > p)] <- 'log2FoldChange'
keyvals[which(abs(res_responders$log2FoldChange) < FC & res_responders$pvalue < p)] <- 'grey25'
names(keyvals)[which(abs(res_responders$log2FoldChange)  < FC & res_responders$pvalue < p)] <- 'pvalue'
keyvals[which(res_responders$log2FoldChange < -FC & res_responders$pvalue < p)] <- 'blue2'
names(keyvals)[which(res_responders$log2FoldChange  < -FC & res_responders$pvalue < p)] <- 'Signif. down-regulated'
keyvals[which(res_responders$log2FoldChange > FC & res_responders$pvalue < p)] <- 'red2'
names(keyvals)[which(res_responders$log2FoldChange > FC & res_responders$pvalue < p)] <- 'Signif. up-regulated'
unique(keyvals)
unique(names(keyvals))



EnhancedVolcano(res_responders,
                lab = rownames(res_responders),
                x = 'log2FoldChange',
                y = 'pvalue',
                selectLab = c("KRT8","KRT18","EPCAM","AGR2","TSPAN8"),
                xlim = c(-8,8),
                xlab = bquote(~Log[2]~ 'fold change'),
                ylab = bquote(~-Log[10] ~ italic(P)),
                title = 'Responders',
                pCutoff = 0.05,
                FCcutoff = 0.5,
                pointSize = 10,
                labSize = 15,
                #shape = c(6, 4, 2, 11, 15),
                colCustom = keyvals,
                colAlpha = 0.75,
                legendPosition = 'right',
                legendLabSize = 40,
                legendIconSize = 30,
                drawConnectors = FALSE,
                widthConnectors = 0.5,
                colConnectors = 'grey50',
                gridlines.major = TRUE,
                gridlines.minor = FALSE,border = 'partial',
                borderWidth = 3,
                borderColour = 'black',boxedLabels=TRUE,titleLabSize = 50,
                subtitleLabSize = 1,
                captionLabSize = 40,axisLabSize = 40)

enter image description here

But I don't know how to reduce the length of x and particularly y axis

I mean I am seeking for a more shrunk plot

Can you help me please?

ADD REPLY • link modified 4 months ago • written 4 months ago by A • 3.7k

Hi all, who did you go from ensemble names to gene names?

ADD REPLY • link written 3 months ago by theodore • 60

See: https://bioinformatics.stackexchange.com/questions/5229/converting-gene-symbol-to-ensembl-id-in-r

ADD REPLY • link modified 3 months ago • written 3 months ago by genomax ♦ 76k

but I got an dds or res list from DeSeq2

ADD REPLY • link written 3 months ago by theodore • 60

......and what is the problem? - you implied that you have Ensembl IDs. These will be either rownames or the first column of your results object.

ADD REPLY • link modified 3 months ago • written 3 months ago by Kevin Blighe ♦ 53k

the code for using the biomart in the posted link to change the ensemble ID o gene names as far as I understand is for matrix. enchancedVolcano uses the dds from Deseq2 OR there is something that I do not understand? Sorry for my ignorance edit: will this fit better A: ensembl id to gene symbol

ADD REPLY • link modified 3 months ago • written 3 months ago by theodore • 60

I developed EnhancedVolcano - it will accept any data coming from any source. At minimum, you just need 2 vectors:

p-values (y-axis)
fold-changes (x-axis)

There does not exist any annotation conversion tool that will accept an entire matrix. They will all accept a vector of gene names that you want to convert. The other tasks (editing the old names and replacing them in your matrix) is your role.

ADD REPLY • link written 3 months ago by Kevin Blighe ♦ 53k

Got it, thought it was only taking a list of sorts. thank you for the clarification. and love the script. saves time from manually writing the code.

ADD REPLY • link written 3 months ago by theodore • 60

---------------------------------------------

Requires

Execution

Example

Parameters

cutoffLineType = 'blank'

cutoffLineType = 'solid'

Similar posts • Search »