Statistic Plot

Visualizes data using various plot types such as bar plots, rose plots, ring plots, pie charts, trend plots, area plots, dot plots, sankey plots, chord plots, venn diagrams, and upset plots.

Usage

StatPlot(
  meta.data,
  stat.by,
  group.by = NULL,
  split.by = NULL,
  bg.by = NULL,
  flip = FALSE,
  NA_color = "grey",
  NA_stat = TRUE,
  keep_empty = FALSE,
  individual = FALSE,
  stat_level = NULL,
  plot_type = c("bar", "rose", "ring", "pie", "trend", "area", "dot", "sankey", "chord",
    "venn", "upset"),
  stat_type = c("percent", "count"),
  position = c("stack", "dodge"),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  bg_palette = "Paired",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  label = FALSE,
  label.size = 3.5,
  label.fg = "black",
  label.bg = "white",
  label.bg.r = 0.1,
  aspect.ratio = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  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

meta.data: The data frame containing the data to be plotted.
stat.by: The column name(s) in meta.data specifying the variable(s) to be plotted.
group.by: The column name in meta.data specifying the grouping variable.
split.by: The column name in meta.data specifying the splitting variable.
bg.by: The column name in meta.data specifying the background variable for bar plots.
flip: Whether to flip the plot. Default is FALSE.
NA_color: The color to use for missing values.
NA_stat: Whether to include missing values in the plot. Default is TRUE.
keep_empty: Whether to keep empty groups in the plot. Default is FALSE.
individual: Whether to plot individual groups separately. Default is FALSE.
stat_level: The level(s) of the variable(s) specified in stat.by to include in the plot. Default is NULL.
plot_type: The type of plot to create. Can be one of "bar", "rose", "ring", "pie", "trend", "area", "dot", "sankey", "chord", "venn", or "upset".
stat_type: The type of statistic to compute for the plot. Can be one of "percent" or "count".
position: The position adjustment for the plot. Can be one of "stack" or "dodge".
palette: The name of the color palette to use for the plot.
palcolor: The color to use in the color palette.
alpha: The transparency level for the plot.
bg_palette: The name of the background color palette to use for bar plots.
bg_palcolor: The color to use in the background color palette.
bg_alpha: The transparency level for the background color in bar plots.
label: Whether to add labels on the plot. Default is FALSE.
label.size: The size of the labels.
label.fg: The foreground color of the labels.
label.bg: The background color of the labels.
label.bg.r: The radius of the rounded corners of the label background.
aspect.ratio: The aspect ratio of the plot.
title: The main title of the plot.
subtitle: The subtitle of the plot.
xlab: The x-axis label of the plot.
ylab: The y-axis label of the plot.
legend.position: The position of the legend in the plot. Can be one of "right", "left", "bottom", "top", or "none".
legend.direction: The direction of the legend in the plot. Can be one of "vertical" or "horizontal".
theme_use: The name of the theme to use for the plot. Can be one of the predefined themes or a custom theme.
theme_args: A list of arguments to be passed to the theme function.
combine: Whether to combine multiple plots into a single plot. Default is TRUE.
nrow: The number of rows in the combined plot. Default is NULL.
ncol: The number of columns in the combined plot. Default is NULL.
byrow: Whether to fill the plot by row or by column. Default is TRUE.
force: Whether to force the plot even if some variables have more than 100 levels. Default is FALSE.
seed: The random seed to use for reproducible results. Default is 11.

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> 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 
meta.data <- pancreas_sub@meta.data
StatPlot(
  meta.data,
  stat.by = "Phase",
  group.by = "CellType",
  plot_type = "bar",
  label = TRUE
)


StatPlot(
  meta.data,
  stat.by = "highly_variable_genes",
  plot_type = "ring",
  label = TRUE,
  NA_stat = FALSE
)
#> Error in StatPlot(meta.data, stat.by = "highly_variable_genes", plot_type = "ring",     label = TRUE, NA_stat = FALSE): Highly_variable_genes is not in the meta.data.

if (FALSE) { # \dontrun{
pancreas_sub <- AnnotateFeatures(
  pancreas_sub,
  species = "Mus_musculus",
  IDtype = "symbol",
  db = c("CSPA", "TF")
)
StatPlot(
  GetFeaturesData(pancreas_sub, "RNA"),
  stat.by = "TF",
  group.by = "CSPA",
  stat_type = "count",
  plot_type = "bar",
  position = "dodge",
  label = TRUE,
  NA_stat = FALSE
)
} # }

Usage

Arguments

See also

Examples