Find Up-regulated genes and Create Volcano Plot for DEG's in R
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4.0 years ago

Hello all, I have calculated differentially expressed genes using an R package splineTimeR, the output is somewhat like :

AveExpr F   P.Value adj.P.Val
AADAC   100.711306333333    16.6604292065194    1.1174207077631e-06 0.000406115715587842
AADACL1 350.521463333333    12.7979620016388    8.83104003501535e-06    0.00198193769928702
AADACL4 48.3962566666667    12.9162206315646    8.23685380308999e-06    0.00187450007973965
ABHD4   154.996276666667    6.81283887808375    0.000645618450667365    0.0382509296422766
ABHD8   264.137053333333    6.46711083379469    0.000878780315793165    0.0469275336824685
ABI3BP  748.711866666667    9.67566832958069    6.69605139823663e-05    0.00834026596280108

which have column definition as following :

AveExprs refers to the average log2-expression
for a probe (representing a gene) over all arrays. The F column contains
moderate F-statistics, P.Value raw p-value and adj.P.Value BenjaminiHochberg adjusted p-value.
  1. How to find significantly Up-Regulated and Down-Regulated genes from the above data ?
  2. How to plot Volcano Plot from the above data?
  3. Is there a way to plot the names of the significantly Up-Regulated genes in the Volcano Plot ? If possible, then how ?
volcano-plot DEG R • 2.2k views
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There is a very nice tutorial here: link or here: link

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Sir, I have seen the tutorial earlier, problem with that tutorial is it doesn't say how to calculate significantly up regulated genes and also I think my outputData doesn't contain any log2FC value. Can you help by explaining a bit more sir ?

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how to calculate significantly up regulated genes?

You already did that. Significantly up- and down-regulated genes are the ones with adj.P.Val < 0.05.

I think my outputData doesn't contain any log2FC value

Pretty sure it doesn't matter. Just change the x axis title.

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thanks a lot sir, one last thing sir, what to use in which column from my output as the code requires:

EnhancedVolcano(res1,
    lab = rownames(res1),
    x = 'log2FoldChange',
    y = 'pvalue',
    xlim = c(-5, 8))

what parameters/arguements from my output should I give to it ?

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I developed this package. The code does not require those values. You choose the values to suit your data. In your case, it would simply be, assuming that your object is called res:

EnhancedVolcano(res,
    lab = rownames(res),
    x = 'F',
    y = 'P.Value')

You can use this package for plotting, for example, pairwise time-point comparisons, like, Time2 vs Time1, Time3 vs Time2, etc.

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Ok, by looking at the splineTimeR tutorial, F is not the fold change and therefore you can't do a Volcano plot. My bad!

Also, since you are working with time-series data, a Volcano Plot is not the right way to visualize the genes that significantly change over the time. For the visualization, I would suggest you to look at the splineTimeR tutorial

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