p-fold plot

Question

[shamza]

I want to construct this plot, and I have already performed the DESeq analysis.

This is how the data looks:

Gene    p_val   avg_logFC   pct.1   pct.2   p_val_adj
HLA-B   1.69E-152   0.719935845 0.993   0.988   2.38E-148
VAMP5   2.73E-97    1.137804386 0.87    0.527   3.85E-93
PSME2   6.25E-88    0.820693535 0.965   0.88    8.80E-84
STAT1   1.03E-83    0.890453249 0.859   0.553   1.45E-79
TMSB10  5.93E-76    0.490543615 0.996   0.997   8.35E-72
B2M 1.33E-75    0.37713743  0.998   0.998   1.87E-71
TYMP    2.49E-72    0.906256415 0.953   0.824   3.50E-68
IFITM3  1.49E-69    0.995476345 0.926   0.798   2.10E-65
RARRES3 4.66E-68    0.837395227 0.834   0.559   6.56E-64
ANKRD22 1.14E-67    0.681502637 0.503   0.083   1.61E-63
PSMB9   1.28E-64    0.659830567 0.933   0.8 1.80E-60
WARS    2.04E-62    0.959950859 0.846   0.558   2.87E-58
UBE2L6  1.99E-61    0.605432484 0.862   0.621   2.80E-57
GBP5    2.85E-61    0.793452491 0.611   0.188   4.01E-57
GBP1    1.88E-56    0.814885385 0.762   0.436   2.64E-52
MT2A    5.05E-53    0.848928354 0.806   0.459   7.11E-49
PSMB8   6.69E-53    0.504554991 0.89    0.738   9.40E-49
RPL26   1.06E-52    -0.448016779    0.959   0.985   1.49E-48
SERPINA1    3.82E-51    0.766048263 0.854   0.639   5.38E-47
RPL17   1.05E-49    -0.459168307    0.899   0.979   1.48E-45
CALHM6  3.13E-47    0.820200941 0.862   0.706   4.40E-43
LAP3    6.07E-44    0.53985539  0.9 0.812   8.54E-40
SERPING1    7.96E-44    0.593358466 0.613   0.286   1.12E-39
GBP4    3.46E-43    0.503697693 0.666   0.332   4.86E-39
RPS15A  2.54E-42    -0.339844264    0.98    0.992   3.58E-38
PSME1   3.14E-42    0.386908546 0.948   0.894   4.42E-38
HLA-DQB1    5.91E-42    -0.719268982    0.924   0.941   8.32E-38
HLA-A   2.99E-40    0.345138642 0.991   0.985   4.20E-36
TNFSF10 1.43E-39    0.577723294 0.767   0.48    2.01E-35
DNASE1L3    2.26E-39    -0.997362611    0.192   0.483   3.18E-35
SNX10   4.41E-39    0.514208907 0.775   0.515   6.20E-35
ISG15   1.07E-38    0.535463063 0.66    0.324   1.51E-34
PSMB10  1.17E-38    0.43369206  0.893   0.814   1.65E-34
RPL13   1.78E-38    -0.275473045    0.986   0.994   2.51E-34
SMCO4   3.64E-38    0.509866752 0.797   0.576   5.12E-34
IRF1    4.18E-38    0.560489754 0.856   0.615   5.88E-34
TAP1    1.52E-37    0.447373643 0.772   0.5 2.14E-33
TGM2    1.78E-37    0.354960954 0.334   0.059   2.51E-33
IDO1    2.32E-36    1.058259387 0.417   0.13    3.26E-32
CST3    5.43E-35    -0.576129784    0.987   0.994   7.64E-31
FCER1G  8.22E-35    0.402186485 0.924   0.903   1.16E-30
CXCL9   6.79E-34    1.230192366 0.333   0.076   9.56E-30
GCH1    9.28E-34    0.429635781 0.541   0.238   1.31E-29
CD38    1.86E-33    0.331142465 0.476   0.186   2.61E-29
RPS16   5.35E-32    -0.25358759 0.972   0.979   7.53E-28

Answer 1

[rpolicastro]

With ggplot and ggrepel. It only shows the gene name for the top and bottom 10 genes (feel free to modify this in the nth code).

library("tidyverse")
library("ggrepel")

df |>
  dplyr::mutate(
    label=ifelse(
      avg_logFC >= nth(avg_logFC, 10, desc(avg_logFC)) | avg_logFC <= nth(avg_logFC, 10, avg_logFC),
      Gene, NA),
    DEGs=dense_rank(-avg_logFC)) |>
  ggplot(aes(x=DEGs, y=avg_logFC)) +
    geom_point(aes(color=avg_logFC), show.legend=FALSE) +
    geom_text_repel(aes(label=label)) +
    geom_hline(yintercept=0, linetype="dashed")

[shamza]

Thank you for responding, however, I am running into another problem when I execute this code in R.

Error in UseMethod("mutate") : no applicable method for 'mutate' applied to an object of class "function"

[rpolicastro]

You need to replace df in the code with your data.frame of results.

[shamza]

Hey, I did change the df with my data frame however, I am still getting an error. The error is as follows:

Error in dplyr::mutate(): ℹ In argument: label = ifelse(...). Caused by error: ! unable to find an inherited method for function ‘desc’ for signature ‘"numeric"’ Run rlang::last_trace() to see where the error occurred.