mp_plot_ord-methods: Plotting the result of PCA, PCoA, CCA, RDA, NDMS or DCA

In xiangpin/MicrobitaProcess: A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework

Plotting the result of PCA, PCoA, CCA, RDA, NDMS or DCA

Description

Plotting the result of PCA, PCoA, CCA, RDA, NDMS or DCA

Usage

mp_plot_ord(
  .data,
  .ord,
  .dim = c(1, 2),
  .group = NULL,
  .starshape = 15,
  .size = 2,
  .alpha = 1,
  .color = "black",
  starstroke = 0.5,
  show.side = TRUE,
  show.adonis = FALSE,
  ellipse = FALSE,
  show.sample = FALSE,
  show.envfit = FALSE,
  p.adjust = NULL,
  filter.envfit = FALSE,
  ...
)

## S4 method for signature 'MPSE'
mp_plot_ord(
  .data,
  .ord,
  .dim = c(1, 2),
  .group = NULL,
  .starshape = 15,
  .size = 2,
  .alpha = 1,
  .color = "black",
  starstroke = 0.5,
  show.side = TRUE,
  show.adonis = FALSE,
  ellipse = FALSE,
  show.sample = FALSE,
  show.envfit = FALSE,
  p.adjust = NULL,
  filter.envfit = FALSE,
  ...
)

## S4 method for signature 'tbl_mpse'
mp_plot_ord(
  .data,
  .ord,
  .dim = c(1, 2),
  .group = NULL,
  .starshape = 15,
  .size = 2,
  .alpha = 1,
  .color = "black",
  starstroke = 0.5,
  show.side = TRUE,
  show.adonis = FALSE,
  ellipse = FALSE,
  show.sample = FALSE,
  show.envfit = FALSE,
  p.adjust = NULL,
  filter.envfit = FALSE,
  ...
)

## S4 method for signature 'grouped_df_mpse'
mp_plot_ord(
  .data,
  .ord,
  .dim = c(1, 2),
  .group = NULL,
  .starshape = 15,
  .size = 2,
  .alpha = 1,
  .color = "black",
  starstroke = 0.5,
  show.side = TRUE,
  show.adonis = FALSE,
  ellipse = FALSE,
  show.sample = FALSE,
  show.envfit = FALSE,
  p.adjust = NULL,
  filter.envfit = FALSE,
  ...
)

Arguments

.data	MPSE or tbl_mpse object, it is required.
.ord	a name of ordination (required), options are PCA, PCoA, DCA, NMDS, RDA, CCA, but the corresponding calculation methods (mp_cal_pca, mp_cal_pcoa, ...) should be done with action="add" before it.
.dim	integer which dimensions will be displayed, it should be a vector (length=2) default is c(1, 2). if the length is one the default will also be displayed.
.group	the column name of variable to be mapped to the color of points (fill character of geom_star) or one specified color code, default is NULL, meaning fill=NA, the points are hollow.
.starshape	the column name of variable to be mapped to the shapes of points (starshape character of geom_star) or one specified starshape of point of ggstar, default is NULL, meaning starshape=15 (circle point).
.size	the column name of variable to be mapped to the size of points (size character of geom_star) or one specified size of point of ggstar, default is NULL, meaning the size=1.5, the size of points.
.alpha	the column name of variable to be mapped to the transparency of points (alpha character of geom_star) or one specified alpha of point of ggstar. default is NULL, meaning the alpha=1, the transparency of points.
.color	the column name of variable to be mapped to the color of line of points (color character of geom_star) or one specified starshape of point of ggstar, default is NULL, meaning the color is 'black'.
starstroke	numeric the width of edge of points, default is 0.5.
show.side	logical whether display the side boxplot with the specified .dim dimensions, default is TRUE.
show.adonis	logical whether display the result of mp_adonis with action='all', default is FALSE.
ellipse	logical, whether to plot ellipses, default is FALSE. (.group or .color variables according to the 'geom', the default geom is path, so .color can be mapped to the corresponding variable).
show.sample	logical, whether display the sample names of points, default is FALSE.
show.envfit	logical, whether display the result after run [mp_envfit()], default is FALSE.
p.adjust	a character method of p.adjust p.adjust, default is NULL, options are 'fdr', 'bonferroni', 'BH' etc.
filter.envfit	logical or numeric, whether to remove the no significant environment factor after run [mp_envfit()], default is FALSE, meaning do not remove. If it is numeric, meaning the keep p.value or the adjust p with p.adjust the factors smaller than the numeric, e.g when filter.envfit=0.05 or (filter.envfit=TRUE), meaning the factors of p <= 0.05 will be displayed.
...	additional parameters, see also the stat_ellipse.

See Also

[mp_cal_pca()], [mp_cal_pcoa], [mp_cal_nmds], [mp_cal_rda], [mp_cal_cca], [mp_envfit()] and [mp_extract_internal_attr()]

Examples

## Not run: 
library(vegan)
data(varespec, varechem)
mpse <- MPSE(assays=list(Abundance=t(varespec)), colData=varechem)
envformula <- paste("~", paste(colnames(varechem), collapse="+")) %>% as.formula
mpse %<>%
mp_cal_cca(.abundance=Abundance, .formula=envformula, action="add") %>%
mp_envfit(.ord=CCA, .env=colnames(varechem), permutations=9999, action="add")
mpse
p1 <- mpse %>% mp_plot_ord(.ord=CCA, .group=Al, .size=Mn)
p1
p2 <- mpse %>% mp_plot_ord(.ord=CCA, .group=Al, .size=Mn, show.sample=TRUE)
p2
p3 <- mpse %>% mp_plot_ord(.ord=CCA, .group="blue", .size=Mn, .alpha=0.8, show.sample=TRUE)
p3
p4 <- mpse %>% mp_plot_ord(.ord=CCA, .group=Al, .size=Mn, show.sample=TRUE, show.envfit=TRUE)
p4

## End(Not run)

xiangpin/MicrobitaProcess documentation built on April 12, 2024, 9:03 p.m.