Generate a volcano plot based on differential expression analysis results.
Usage
VolcanoPlot(
srt,
group_by = NULL,
test.use = "wilcox",
DE_threshold = "avg_log2FC > 0 & p_val_adj < 0.05",
x_metric = "diff_pct",
palette = "RdBu",
palcolor = NULL,
pt.size = 1,
pt.alpha = 1,
cols.highlight = "black",
sizes.highlight = 1,
alpha.highlight = 1,
stroke.highlight = 0.5,
nlabel = 5,
features_label = NULL,
label.fg = "black",
label.bg = "white",
label.bg.r = 0.1,
label.size = 4,
aspect.ratio = NULL,
xlab = x_metric,
ylab = "-log10(p-adjust)",
theme_use = "theme_scop",
theme_args = list(),
combine = TRUE,
nrow = NULL,
ncol = NULL,
byrow = TRUE
)Arguments
- srt
An object of class
Seuratcontaining the results of differential expression analysis.- group_by
A character vector specifying the column in
srtto group the samples by. Default isNULL.- test.use
A character string specifying the type of statistical test to use. Default is
"wilcox".- DE_threshold
A character string specifying the threshold for differential expression. Default is
"avg_log2FC > 0 & p_val_adj < 0.05".- x_metric
A character string specifying the metric to use for the x-axis. Default is
"diff_pct".- palette
A character string specifying the color palette to use for the plot. Default is
"RdBu".- palcolor
A character string specifying the color for the palette. Default is
NULL.- pt.size
The size of the points. Default is
1.- pt.alpha
The transparency of the points. Default is
1.- cols.highlight
A character string specifying the color for highlighted points. Default is
"black".- sizes.highlight
The size of the highlighted points. Default is
1.- alpha.highlight
The transparency of the highlighted points. Default is
1.- stroke.highlight
The stroke width for the highlighted points. Default is
0.5.- nlabel
An integer value specifying the number of labeled points per group. Default is
5.- features_label
A character vector specifying the feature labels to plot. Default is
NULL.- label.fg
A character string specifying the color for the labels' foreground. Default is
"black".- label.bg
A character string specifying the color for the labels' background. Default is
"white".- label.bg.r
The radius of the rounding of the labels' background. Default is 0.1.
- label.size
The size of the labels. Default is
4.- aspect.ratio
The aspect ratio of the plot. Default is
NULL.- xlab
A character string specifying the x-axis label. Default is the value of
x_metric.- ylab
A character string specifying the y-axis label. Default is
"-log10(p-adjust)".- theme_use
A character string specifying the theme to use for the plot. Default is
"theme_scop".- theme_args
A list of theme arguments to pass to the
theme_usefunction. Default is an empty list.- combine
Whether to combine the plots for each group into a single plot. Default is
TRUE.- nrow
An integer value specifying the number of rows in the combined plot. Default is
NULL.- ncol
An integer value specifying the number of columns in the combined plot. Default is
NULL.- byrow
Whether to arrange the plots by row in the combined plot. Default is
TRUE.
Examples
data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2025-09-20 14:00:59] Start standard scop workflow...
#> ℹ [2025-09-20 14:01:00] Checking a list of <Seurat> object...
#> ! [2025-09-20 14:01:00] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 14:01:00] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#> ℹ [2025-09-20 14:01:02] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#> ℹ [2025-09-20 14:01:03] Use the separate HVF from srt_list
#> ℹ [2025-09-20 14:01:03] Number of available HVF: 2000
#> ℹ [2025-09-20 14:01:03] Finished check
#> ℹ [2025-09-20 14:01:04] Perform `Seurat::ScaleData()`
#> Warning: Different features in new layer data than already exists for scale.data
#> ℹ [2025-09-20 14:01:04] Perform pca linear dimension reduction
#> StandardPC_ 1
#> Positive: Aplp1, Cpe, Gnas, Fam183b, Map1b, Hmgn3, Pcsk1n, Chga, Tuba1a, Bex2
#> Syt13, Isl1, 1700086L19Rik, Pax6, Chgb, Scgn, Rbp4, Scg3, Gch1, Camk2n1
#> Cryba2, Pcsk2, Pyy, Tspan7, Mafb, Hist3h2ba, Dbpht2, Abcc8, Rap1b, Slc38a5
#> Negative: Spp1, Anxa2, Sparc, Dbi, 1700011H14Rik, Wfdc2, Gsta3, Adamts1, Clu, Mgst1
#> Bicc1, Ldha, Vim, Cldn3, Cyr61, Rps2, Mt1, Ptn, Phgdh, Nudt19
#> Smtnl2, Smco4, Habp2, Mt2, Col18a1, Rpl12, Galk1, Cldn10, Acot1, Ccnd1
#> StandardPC_ 2
#> Positive: Rbp4, Tagln2, Tuba1b, Fkbp2, Pyy, Pcsk2, Iapp, Tmem27, Meis2, Tubb4b
#> Pcsk1n, Dbpht2, Rap1b, Dynll1, Tubb2a, Sdf2l1, Scgn, 1700086L19Rik, Scg2, Abcc8
#> Atp1b1, Hspa5, Fam183b, Papss2, Slc38a5, Scg3, Mageh1, Tspan7, Ppp1r1a, Ociad2
#> Negative: Neurog3, Btbd17, Gadd45a, Ppp1r14a, Neurod2, Sox4, Smarcd2, Mdk, Pax4, Btg2
#> Sult2b1, Hes6, Grasp, Igfbpl1, Gpx2, Cbfa2t3, Foxa3, Shf, Mfng, Tmsb4x
#> Amotl2, Gdpd1, Cdc14b, Epb42, Rcor2, Cotl1, Upk3bl, Rbfox3, Cldn6, Cer1
#> StandardPC_ 3
#> Positive: Nusap1, Top2a, Birc5, Aurkb, Cdca8, Pbk, Mki67, Tpx2, Plk1, Ccnb1
#> 2810417H13Rik, Incenp, Cenpf, Ccna2, Prc1, Racgap1, Cdk1, Aurka, Cdca3, Hmmr
#> Spc24, Kif23, Sgol1, Cenpe, Cdc20, Hist1h1b, Cdca2, Mxd3, Kif22, Ska1
#> Negative: Anxa5, Pdzk1ip1, Acot1, Tpm1, Anxa2, Dcdc2a, Capg, Sparc, Ttr, Pamr1
#> Clu, Cxcl12, Ndrg2, Hnf1aos1, Gas6, Gsta3, Krt18, Ces1d, Atp1b1, Muc1
#> Hhex, Acadm, Spp1, Enpp2, Bcl2l14, Sat1, Smtnl2, 1700011H14Rik, Tgm2, Fam159a
#> StandardPC_ 4
#> Positive: Glud1, Tm4sf4, Akr1c19, Cldn4, Runx1t1, Fev, Pou3f4, Gm43861, Pgrmc1, Arx
#> Cd200, Lrpprc, Hmgn3, Ppp1r14c, Pam, Etv1, Tsc22d1, Slc25a5, Akap17b, Pgf
#> Fam43a, Emb, Jun, Krt8, Dnajc12, Mid1ip1, Ids, Rgs17, Uchl1, Alcam
#> Negative: Ins2, Ins1, Ppp1r1a, Nnat, Calr, Sytl4, Sdf2l1, Iapp, Pdia6, Mapt
#> G6pc2, C2cd4b, Npy, Gng12, P2ry1, Ero1lb, Adra2a, Papss2, Arhgap36, Fam151a
#> Dlk1, Creld2, Gip, Tmem215, Gm27033, Cntfr, Prss53, C2cd4a, Lyve1, Ociad2
#> StandardPC_ 5
#> Positive: Pdx1, Nkx6-1, Npepl1, Cldn4, Cryba2, Fev, Jun, Chgb, Gng12, Adra2a
#> Mnx1, Sytl4, Pdk3, Gm27033, Nnat, Chga, Ins2, 1110012L19Rik, Enho, Krt7
#> Mlxipl, Tmsb10, Flrt1, Pax4, Tubb3, Prrg2, Gars, Frzb, BC023829, Gm2694
#> Negative: Irx2, Irx1, Gcg, Ctxn2, Tmem27, Ctsz, Tmsb15l, Nap1l5, Pou6f2, Gria2
#> Ghrl, Peg10, Smarca1, Arx, Lrpap1, Rgs4, Ttr, Gast, Tmsb15b2, Serpina1b
#> Slc16a10, Wnk3, Ly6e, Auts2, Sct, Arg1, Dusp10, Sphkap, Dock11, Edn3
#> ℹ [2025-09-20 14:01:05] Perform `Seurat::FindClusters()` with louvain and `cluster_resolution` = 0.6
#> ℹ [2025-09-20 14:01:05] Reorder clusters...
#> ! [2025-09-20 14:01:05] Using `Seurat::AggregateExpression()` to calculate pseudo-bulk data for <Assay5>
#> ℹ [2025-09-20 14:01:05] Perform umap nonlinear dimension reduction
#> ℹ [2025-09-20 14:01:05] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2025-09-20 14:01:05] UMAP will return its model
#> ℹ [2025-09-20 14:01:10] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2025-09-20 14:01:10] UMAP will return its model
#> ✔ [2025-09-20 14:01:14] Run scop standard workflow done
pancreas_sub <- RunDEtest(
pancreas_sub,
group_by = "CellType"
)
#> ℹ [2025-09-20 14:01:14] immunogenomics/presto installed successfully
#> ℹ [2025-09-20 14:01:15] Data type is log-normalized
#> ℹ [2025-09-20 14:01:15] Start differential expression test
#> ℹ [2025-09-20 14:01:15] Find all markers(wilcox) among 5 groups...
#> ℹ [2025-09-20 14:01:15] Using 1 core
#> ⠙ [2025-09-20 14:01:15] Running [1/5] ETA: 1s
#> ⠹ [2025-09-20 14:01:15] Running [3/5] ETA: 0s
#> ✔ [2025-09-20 14:01:15] Completed 5 tasks in 951ms
#>
#> ℹ [2025-09-20 14:01:16] Building results
#> ✔ [2025-09-20 14:01:16] Differential expression test completed
VolcanoPlot(
pancreas_sub,
group_by = "CellType",
ncol = 2
)
VolcanoPlot(
pancreas_sub,
group_by = "CellType",
DE_threshold = "abs(diff_pct) > 0.3 & p_val_adj < 0.05",
ncol = 2
)
VolcanoPlot(
pancreas_sub,
group_by = "CellType",
x_metric = "avg_log2FC",
ncol = 2
)
