This function generates a statistical plot for features.
Usage
FeatureStatPlot(
srt,
stat.by,
group.by = NULL,
split.by = NULL,
bg.by = NULL,
plot.by = c("group", "feature"),
fill.by = c("group", "feature", "expression"),
cells = NULL,
layer = "data",
assay = NULL,
keep_empty = FALSE,
individual = FALSE,
plot_type = c("violin", "box", "bar", "dot", "col"),
palette = "Paired",
palcolor = NULL,
alpha = 1,
bg_palette = "Paired",
bg_palcolor = NULL,
bg_alpha = 0.2,
add_box = FALSE,
box_color = "black",
box_width = 0.1,
box_ptsize = 2,
add_point = FALSE,
pt.color = "grey30",
pt.size = NULL,
pt.alpha = 1,
jitter.width = 0.4,
jitter.height = 0.1,
add_trend = FALSE,
trend_color = "black",
trend_linewidth = 1,
trend_ptsize = 2,
add_stat = c("none", "mean", "median"),
stat_color = "black",
stat_size = 1,
stat_stroke = 1,
stat_shape = 25,
add_line = NULL,
line_color = "red",
line_size = 1,
line_type = 1,
cells.highlight = NULL,
cols.highlight = "red",
sizes.highlight = 1,
alpha.highlight = 1,
calculate_coexp = FALSE,
same.y.lims = FALSE,
y.min = NULL,
y.max = NULL,
y.trans = "identity",
y.nbreaks = 5,
sort = FALSE,
stack = FALSE,
flip = FALSE,
comparisons = NULL,
ref_group = NULL,
pairwise_method = "wilcox.test",
multiplegroup_comparisons = FALSE,
multiple_method = "kruskal.test",
sig_label = c("p.signif", "p.format"),
sig_labelsize = 3.5,
aspect.ratio = NULL,
title = NULL,
subtitle = NULL,
xlab = NULL,
ylab = "Expression level",
legend.position = "right",
legend.direction = "vertical",
theme_use = "theme_scop",
theme_args = list(),
combine = TRUE,
nrow = NULL,
ncol = NULL,
byrow = TRUE,
force = FALSE,
seed = 11
)Arguments
- srt
A Seurat object.
- stat.by
A character vector specifying the features to plot.
- group.by
A character vector specifying the groups to group by. Default is NULL.
- split.by
A character vector specifying the variable to split the plot by. Default is NULL.
- bg.by
A character vector specifying the variable to use as the background color. Default is NULL.
- plot.by
A character vector specifying how to plot the data, by group or feature. Possible values are "group", "feature". Default is "group".
- fill.by
A string specifying what to fill the plot by. Possible values are "group", "feature", or "expression". Default is "group".
- cells
A character vector specifying the cells to include in the plot. Default is NULL.
- layer
A string specifying which layer of the Seurat object to use. Default is "data".
- assay
A string specifying which assay to use. Default is NULL.
- keep_empty
Whether to keep empty levels in the plot. Default is FALSE.
- individual
Whether to create individual plots for each group. Default is FALSE.
- plot_type
A string specifying the type of plot to create. Possible values are "violin", "box", "bar", "dot", or "col". Default is "violin".
- palette
A string specifying the color palette to use for filling. Default is "Paired".
- palcolor
A character vector specifying specific colors to use for filling. Default is NULL.
- alpha
The transparency of the plot. Default is 1.
- bg_palette
A string specifying the color palette to use for the background. Default is "Paired".
- bg_palcolor
A character vector specifying specific colors to use for the background. Default is NULL.
- bg_alpha
The transparency of the background. Default is 0.2.
- add_box
Whether to add a box plot to the plot. Default is FALSE.
- box_color
A string specifying the color of the box plot. Default is "black".
- box_width
The width of the box plot. Default is 0.1.
- box_ptsize
The size of the points of the box plot. Default is 2.
- add_point
Whether to add individual data points to the plot. Default is FALSE.
- pt.color
A string specifying the color of the data points. Default is "grey30".
- pt.size
The size of the data points. If NULL, the size is automatically determined. Default is NULL.
- pt.alpha
The transparency of the data points. Default is 1.
- jitter.width
The width of the jitter. Default is 0.5.
- jitter.height
The height of the jitter. Default is 0.1.
- add_trend
Whether to add a trend line to the plot. Default is FALSE.
- trend_color
A string specifying the color of the trend line. Default is "black".
- trend_linewidth
The width of the trend line. Default is 1.
- trend_ptsize
The size of the points of the trend line. Default is 2.
- add_stat
A string specifying which statistical summary to add to the plot. Possible values are "none", "mean", or "median". Default is "none".
- stat_color
A string specifying the color of the statistical summary. Default is "black".
- stat_size
The size of the statistical summary. Default is 1.
- stat_stroke
The stroke width of the statistical summary. Default is 1.
- stat_shape
The shape of the statistical summary. Default is 25.
- add_line
The y-intercept for adding a horizontal line. Default is NULL.
- line_color
A string specifying the color of the horizontal line. Default is "red".
- line_size
The width of the horizontal line. Default is 1.
- line_type
The type of the horizontal line. Default is 1.
- cells.highlight
A logical or character vector specifying the cells to highlight in the plot. If TRUE, all cells are highlighted. If FALSE, no cells are highlighted. Default is NULL.
- cols.highlight
A string specifying the color of the highlighted cells. Default is "red".
- sizes.highlight
The size of the highlighted cells. Default is 1.
- alpha.highlight
The transparency of the highlighted cells. Default is 1.
- calculate_coexp
Whether to calculate co-expression values. Default is FALSE.
- same.y.lims
Whether to use the same y-axis limits for all plots. Default is FALSE.
- y.min
A numeric or character value specifying the minimum y-axis limit. If a character value is provided, it must be of the form "qN" where N is a number between 0 and 100 (inclusive) representing the quantile to use for the limit. Default is NULL.
- y.max
A numeric or character value specifying the maximum y-axis limit. If a character value is provided, it must be of the form "qN" where N is a number between 0 and 100 (inclusive) representing the quantile to use for the limit. Default is NULL.
- y.trans
A string specifying the transformation to apply to the y-axis. Possible values are "identity" or "log2". Default is "identity".
- y.nbreaks
A number of breaks to use for the y-axis. Default is 5.
- sort
A logical or character value specifying whether to sort the groups on the x-axis. If TRUE, groups are sorted in increasing order. If FALSE, groups are not sorted. If "increasing", groups are sorted in increasing order. If "decreasing", groups are sorted in decreasing order. Default is FALSE.
- stack
A logical specifying whether to stack the plots on top of each other. Default is FALSE.
- flip
A logical specifying whether to flip the plot vertically. Default is FALSE.
- comparisons
A list of length-2 vectors. The entries in the vector are either the names of 2 values on the x-axis or the 2 integers that correspond to the index of the groups of interest, to be compared.
- ref_group
A string specifying the reference group for pairwise comparisons. Default is NULL.
- pairwise_method
Method to use for pairwise comparisons. Default is "wilcox.test".
- multiplegroup_comparisons
Whether to add multiple group comparisons to the plot. Default is FALSE.
- multiple_method
Method to use for multiple group comparisons. Default is "kruskal.test".
- sig_label
A string specifying the label to use for significant comparisons. Possible values are "p.signif" or "p.format". Default is "p.format".
- sig_labelsize
The size of the significant comparison labels. Default is 3.5.
- aspect.ratio
The aspect ratio of the plot. Default is NULL.
- title
A string specifying the title of the plot. Default is NULL.
- subtitle
A string specifying the subtitle of the plot. Default is NULL.
- xlab
A string specifying the label of the x-axis. Default is NULL.
- ylab
A string specifying the label of the y-axis. Default is "Expression level".
- legend.position
A string specifying the position of the legend. Possible values are "right", "left", "top", "bottom", or "none". Default is "right".
- legend.direction
A string specifying the direction of the legend. Possible values are "vertical" or "horizontal". Default is "vertical".
- theme_use
A string specifying the theme to use for the plot. Default is "theme_scop".
- theme_args
A list of arguments to pass to the theme function. Default is an empty list.
- combine
Whether to combine the individual plots into a single plot. Default is TRUE.
- nrow
A number of rows for the combined plot. Default is NULL.
- ncol
A number of columns for the combined plot. Default is NULL.
- byrow
A logical specifying whether to fill the combined plot by row or by column. Default is TRUE.
- force
Whether to force the plot creation even if there are more than 100 levels in a variable. Default is FALSE.
- seed
An integer specifying the random seed to use for generating jitter. Default is 11.
Examples
data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2025-09-20 13:21:15] Start standard scop workflow...
#> ℹ [2025-09-20 13:21:16] Checking a list of <Seurat> object...
#> ! [2025-09-20 13:21:16] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 13:21:16] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#> ℹ [2025-09-20 13:21:18] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#> ℹ [2025-09-20 13:21:18] Use the separate HVF from srt_list
#> ℹ [2025-09-20 13:21:19] Number of available HVF: 2000
#> ℹ [2025-09-20 13:21:19] Finished check
#> ℹ [2025-09-20 13:21:19] Perform `Seurat::ScaleData()`
#> Warning: Different features in new layer data than already exists for scale.data
#> ℹ [2025-09-20 13:21:19] 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 13:21:20] Perform `Seurat::FindClusters()` with louvain and `cluster_resolution` = 0.6
#> ℹ [2025-09-20 13:21:20] Reorder clusters...
#> ! [2025-09-20 13:21:20] Using `Seurat::AggregateExpression()` to calculate pseudo-bulk data for <Assay5>
#> ℹ [2025-09-20 13:21:20] Perform umap nonlinear dimension reduction
#> ℹ [2025-09-20 13:21:20] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2025-09-20 13:21:20] UMAP will return its model
#> ℹ [2025-09-20 13:21:24] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2025-09-20 13:21:24] UMAP will return its model
#> ✔ [2025-09-20 13:21:28] Run scop standard workflow done
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType"
) %>% panel_fix(height = 1, width = 2)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
plot_type = "box"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
plot_type = "bar"
)
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
plot_type = "dot"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
plot_type = "col"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
add_box = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
add_point = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
add_trend = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
add_stat = "mean"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
add_line = 0.2,
line_type = 2
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
split.by = "Phase"
)
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
split.by = "Phase",
add_box = TRUE,
add_trend = TRUE
)
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("G2M_score", "Fev"),
group.by = "SubCellType",
split.by = "Phase",
comparisons = TRUE
)
#> ℹ [2025-09-20 13:21:41] Installing: ggpubr...
#>
#> → Will install 26 packages.
#> → All 26 packages (0 B) are cached.
#> + Deriv 4.2.0
#> + MatrixModels 0.5-4
#> + Rdpack 2.6.4
#> + SparseM 1.84-2
#> + abind 1.4-8
#> + broom 1.0.10
#> + car 3.1-3
#> + carData 3.0-5
#> + corrplot 0.95
#> + doBy 4.7.0
#> + ggpubr 0.6.1
#> + ggsci 3.2.0
#> + ggsignif 0.6.4
#> + gridExtra 2.3
#> + lme4 1.1-37
#> + microbenchmark 1.5.0
#> + minqa 1.2.8 + ✔ make
#> + modelr 0.1.11
#> + nloptr 2.2.1 + ✔ cmake
#> + numDeriv 2016.8-1.1
#> + pbkrtest 0.5.5
#> + polynom 1.4-1
#> + quantreg 6.1
#> + rbibutils 2.3
#> + reformulas 0.4.1
#> + rstatix 0.7.2
#> ✔ All system requirements are already installed.
#>
#> ℹ No downloads are needed, 26 pkgs are cached
#> ✔ Got abind 1.4-8 (x86_64-pc-linux-gnu-ubuntu-24.04) (64.92 kB)
#> ✔ Got Deriv 4.2.0 (x86_64-pc-linux-gnu-ubuntu-24.04) (152.58 kB)
#> ✔ Got minqa 1.2.8 (x86_64-pc-linux-gnu-ubuntu-24.04) (122.60 kB)
#> ✔ Got microbenchmark 1.5.0 (x86_64-pc-linux-gnu-ubuntu-24.04) (65.96 kB)
#> ✔ Got nloptr 2.2.1 (x86_64-pc-linux-gnu-ubuntu-24.04) (567.65 kB)
#> ✔ Got rstatix 0.7.2 (x86_64-pc-linux-gnu-ubuntu-24.04) (616.65 kB)
#> ✔ Got ggsignif 0.6.4 (x86_64-pc-linux-gnu-ubuntu-24.04) (602.07 kB)
#> ✔ Got MatrixModels 0.5-4 (x86_64-pc-linux-gnu-ubuntu-24.04) (408.50 kB)
#> ✔ Got pbkrtest 0.5.5 (x86_64-pc-linux-gnu-ubuntu-24.04) (222.06 kB)
#> ✔ Got modelr 0.1.11 (x86_64-pc-linux-gnu-ubuntu-24.04) (200.70 kB)
#> ✔ Got car 3.1-3 (x86_64-pc-linux-gnu-ubuntu-24.04) (1.54 MB)
#> ✔ Got carData 3.0-5 (x86_64-pc-linux-gnu-ubuntu-24.04) (1.70 MB)
#> ✔ Got Rdpack 2.6.4 (x86_64-pc-linux-gnu-ubuntu-24.04) (637.80 kB)
#> ✔ Got SparseM 1.84-2 (x86_64-pc-linux-gnu-ubuntu-24.04) (887.98 kB)
#> ✔ Got rbibutils 2.3 (x86_64-pc-linux-gnu-ubuntu-24.04) (1.14 MB)
#> ✔ Got numDeriv 2016.8-1.1 (x86_64-pc-linux-gnu-ubuntu-24.04) (114.36 kB)
#> ✔ Got ggpubr 0.6.1 (x86_64-pc-linux-gnu-ubuntu-24.04) (2.12 MB)
#> ✔ Got polynom 1.4-1 (x86_64-pc-linux-gnu-ubuntu-24.04) (406.99 kB)
#> ✔ Got corrplot 0.95 (x86_64-pc-linux-gnu-ubuntu-24.04) (3.82 MB)
#> ✔ Got reformulas 0.4.1 (x86_64-pc-linux-gnu-ubuntu-24.04) (134.90 kB)
#> ✔ Got gridExtra 2.3 (x86_64-pc-linux-gnu-ubuntu-24.04) (1.11 MB)
#> ✔ Got ggsci 3.2.0 (x86_64-pc-linux-gnu-ubuntu-24.04) (2.40 MB)
#> ✔ Got quantreg 6.1 (x86_64-pc-linux-gnu-ubuntu-24.04) (1.46 MB)
#> ✔ Got lme4 1.1-37 (x86_64-pc-linux-gnu-ubuntu-24.04) (4.28 MB)
#> ✔ Got doBy 4.7.0 (x86_64-pc-linux-gnu-ubuntu-24.04) (4.91 MB)
#> ℹ Installing system requirements
#> ℹ Executing `sudo sh -c apt-get -y update`
#> Get:1 file:/etc/apt/apt-mirrors.txt Mirrorlist [144 B]
#> Hit:2 http://azure.archive.ubuntu.com/ubuntu noble InRelease
#> Hit:6 https://packages.microsoft.com/repos/azure-cli noble InRelease
#> Get:3 http://azure.archive.ubuntu.com/ubuntu noble-updates InRelease [126 kB]
#> Hit:7 https://packages.microsoft.com/ubuntu/24.04/prod noble InRelease
#> Get:4 http://azure.archive.ubuntu.com/ubuntu noble-backports InRelease [126 kB]
#> Get:5 http://azure.archive.ubuntu.com/ubuntu noble-security InRelease [126 kB]
#> Get:8 http://azure.archive.ubuntu.com/ubuntu noble-updates/main amd64 Packages [1415 kB]
#> Get:9 http://azure.archive.ubuntu.com/ubuntu noble-updates/main amd64 Components [175 kB]
#> Get:10 http://azure.archive.ubuntu.com/ubuntu noble-updates/universe amd64 Packages [1485 kB]
#> Get:11 http://azure.archive.ubuntu.com/ubuntu noble-updates/universe amd64 Components [377 kB]
#> Get:12 http://azure.archive.ubuntu.com/ubuntu noble-updates/restricted amd64 Components [212 B]
#> Get:13 http://azure.archive.ubuntu.com/ubuntu noble-updates/multiverse amd64 Components [940 B]
#> Get:14 http://azure.archive.ubuntu.com/ubuntu noble-backports/main amd64 Components [7080 B]
#> Get:15 http://azure.archive.ubuntu.com/ubuntu noble-backports/universe amd64 Components [19.2 kB]
#> Get:16 http://azure.archive.ubuntu.com/ubuntu noble-backports/restricted amd64 Components [216 B]
#> Get:17 http://azure.archive.ubuntu.com/ubuntu noble-backports/multiverse amd64 Components [212 B]
#> Get:18 http://azure.archive.ubuntu.com/ubuntu noble-security/main amd64 Components [21.5 kB]
#> Get:19 http://azure.archive.ubuntu.com/ubuntu noble-security/universe amd64 Components [52.2 kB]
#> Get:20 http://azure.archive.ubuntu.com/ubuntu noble-security/restricted amd64 Components [212 B]
#> Get:21 http://azure.archive.ubuntu.com/ubuntu noble-security/multiverse amd64 Components [212 B]
#> Fetched 3933 kB in 1s (6102 kB/s)
#> Reading package lists...
#> ℹ Executing `sudo sh -c apt-get -y install make cmake libicu-dev`
#> Reading package lists...
#> Building dependency tree...
#> Reading state information...
#> make is already the newest version (4.3-4.1build2).
#> cmake is already the newest version (3.28.3-1build7).
#> libicu-dev is already the newest version (74.2-1ubuntu3.1).
#> 0 upgraded, 0 newly installed, 0 to remove and 41 not upgraded.
#> ✔ Installed abind 1.4-8 (53ms)
#> ✔ Installed broom 1.0.10 (94ms)
#> ✔ Installed car 3.1-3 (139ms)
#> ✔ Installed carData 3.0-5 (159ms)
#> ✔ Installed corrplot 0.95 (98ms)
#> ✔ Installed Deriv 4.2.0 (116ms)
#> ✔ Installed doBy 4.7.0 (76ms)
#> ✔ Installed ggpubr 0.6.1 (64ms)
#> ✔ Installed ggsci 3.2.0 (63ms)
#> ✔ Installed ggsignif 0.6.4 (62ms)
#> ✔ Installed gridExtra 2.3 (61ms)
#> ✔ Installed lme4 1.1-37 (65ms)
#> ✔ Installed MatrixModels 0.5-4 (121ms)
#> ✔ Installed microbenchmark 1.5.0 (68ms)
#> ✔ Installed minqa 1.2.8 (60ms)
#> ✔ Installed modelr 0.1.11 (60ms)
#> ✔ Installed nloptr 2.2.1 (63ms)
#> ✔ Installed numDeriv 2016.8-1.1 (60ms)
#> ✔ Installed pbkrtest 0.5.5 (92ms)
#> ✔ Installed polynom 1.4-1 (116ms)
#> ✔ Installed quantreg 6.1 (66ms)
#> ✔ Installed rbibutils 2.3 (62ms)
#> ✔ Installed Rdpack 2.6.4 (62ms)
#> ✔ Installed reformulas 0.4.1 (61ms)
#> ✔ Installed rstatix 0.7.2 (61ms)
#> ✔ Installed SparseM 1.84-2 (82ms)
#> ✔ 1 pkg + 66 deps: kept 39, added 26, dld 25 (29.68 MB) [9.4s]
#> ℹ [2025-09-20 13:21:50] ggpubr installed successfully
#> ℹ [2025-09-20 13:21:50] Detected more than 2 groups. Use multiple_method for comparison
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> ℹ [2025-09-20 13:21:50] Detected more than 2 groups. Use multiple_method for comparison
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Rbp4", "Pyy"),
group.by = "SubCellType",
fill.by = "expression",
palette = "Blues",
same.y.lims = TRUE
)
FeatureStatPlot(
pancreas_sub,
stat.by = c("Rbp4", "Pyy"),
group.by = "SubCellType",
multiplegroup_comparisons = TRUE
)
#> ℹ [2025-09-20 13:21:53] ggpubr installed successfully
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Rbp4", "Pyy"),
group.by = "SubCellType",
comparisons = list(c("Alpha", "Beta"), c("Alpha", "Delta"))
)
#> ℹ [2025-09-20 13:21:54] ggpubr installed successfully
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Rbp4", "Pyy"),
group.by = "SubCellType",
comparisons = list(c("Alpha", "Beta"), c("Alpha", "Delta")),
sig_label = "p.format"
)
#> ℹ [2025-09-20 13:21:56] ggpubr installed successfully
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Rbp4", "Pyy"),
group.by = "SubCellType",
bg.by = "CellType",
add_box = TRUE, stack = TRUE
)
FeatureStatPlot(
pancreas_sub,
stat.by = c(
"Sox9", "Anxa2", "Bicc1", # Ductal
"Neurog3", "Hes6", # EPs
"Fev", "Neurod1", # Pre-endocrine
"Rbp4", "Pyy", # Endocrine
"Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
),
legend.position = "top",
legend.direction = "horizontal",
group.by = "SubCellType",
bg.by = "CellType",
stack = TRUE
)
FeatureStatPlot(
pancreas_sub,
stat.by = c(
"Sox9", "Anxa2", "Bicc1", # Ductal
"Neurog3", "Hes6", # EPs
"Fev", "Neurod1", # Pre-endocrine
"Rbp4", "Pyy", # Endocrine
"Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
),
fill.by = "feature",
plot_type = "box",
group.by = "SubCellType",
bg.by = "CellType", stack = TRUE, flip = TRUE
) %>% panel_fix_overall(
width = 8, height = 5
)
# As the plot is created by combining,
# we can adjust the overall height and width directly.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Neurog3", "Rbp4", "Ins1"),
group.by = "CellType",
plot.by = "group"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Neurog3", "Rbp4", "Ins1"),
group.by = "CellType",
plot.by = "feature"
)
#> ℹ [2025-09-20 13:22:08] Setting 'group.by' to 'Features' as 'plot.by' is set to 'feature'
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Neurog3", "Rbp4", "Ins1"),
group.by = "CellType",
plot.by = "feature",
multiplegroup_comparisons = TRUE,
sig_label = "p.format",
sig_labelsize = 4
)
#> ℹ [2025-09-20 13:22:10] Setting 'group.by' to 'Features' as 'plot.by' is set to 'feature'
#> ℹ [2025-09-20 13:22:10] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:10] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:10] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:11] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:11] ggpubr installed successfully
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
FeatureStatPlot(
pancreas_sub,
stat.by = c("Neurog3", "Rbp4", "Ins1"),
group.by = "CellType",
plot.by = "feature",
comparisons = list(c("Neurog3", "Rbp4"), c("Rbp4", "Ins1")),
stack = TRUE
)
#> ℹ [2025-09-20 13:22:13] Setting 'group.by' to 'Features' as 'plot.by' is set to 'feature'
#> ℹ [2025-09-20 13:22:13] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:13] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:13] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:14] ggpubr installed successfully
#> ℹ [2025-09-20 13:22:14] ggpubr installed successfully
FeatureStatPlot(pancreas_sub,
stat.by = c(
"Sox9", "Anxa2", "Bicc1", # Ductal
"Neurog3", "Hes6", # EPs
"Fev", "Neurod1", # Pre-endocrine
"Rbp4", "Pyy", # Endocrine
"Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
), group.by = "SubCellType",
plot.by = "feature",
stack = TRUE
)
#> ℹ [2025-09-20 13:22:16] Setting 'group.by' to 'Features' as 'plot.by' is set to 'feature'
data <- GetAssayData5(
pancreas_sub,
assay = "RNA",
layer = "data",
verbose = FALSE
)
pancreas_sub <- SeuratObject::SetAssayData(
object = pancreas_sub,
layer = "scale.data",
assay = "RNA",
new.data = thisutils::as_matrix(data / rowMeans(data))
)
#> Error in rowMeans(data): 'x' must be an array of at least two dimensions
FeatureStatPlot(
pancreas_sub,
stat.by = c("Neurog3", "Rbp4"),
group.by = "CellType",
layer = "scale.data",
ylab = "FoldChange",
same.y.lims = TRUE,
y.max = 4
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
