mp_plot_abundance-methods: plotting the abundance of taxa via specified taxonomy class

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

plotting the abundance of taxa via specified taxonomy class

Description

plotting the abundance of taxa via specified taxonomy class

Usage

mp_plot_abundance(
  .data,
  .abundance = NULL,
  .group = NULL,
  taxa.class = NULL,
  topn = 10,
  relative = TRUE,
  force = FALSE,
  plot.group = FALSE,
  geom = "flowbar",
  feature.dist = "bray",
  feature.hclust = "average",
  sample.dist = "bray",
  sample.hclust = "average",
  .sec.group = NULL,
  rmun = FALSE,
  rm.zero = TRUE,
  order.by.feature = FALSE,
  ...
)

## S4 method for signature 'MPSE'
mp_plot_abundance(
  .data,
  .abundance = NULL,
  .group = NULL,
  taxa.class = NULL,
  topn = 10,
  relative = TRUE,
  force = FALSE,
  plot.group = FALSE,
  geom = "flowbar",
  feature.dist = "bray",
  feature.hclust = "average",
  sample.dist = "bray",
  sample.hclust = "average",
  .sec.group = NULL,
  rmun = FALSE,
  rm.zero = TRUE,
  order.by.feature = FALSE,
  ...
)

## S4 method for signature 'tbl_mpse'
mp_plot_abundance(
  .data,
  .abundance = NULL,
  .group = NULL,
  taxa.class = NULL,
  topn = 10,
  relative = TRUE,
  force = FALSE,
  plot.group = FALSE,
  geom = "flowbar",
  feature.dist = "bray",
  feature.hclust = "average",
  sample.dist = "bray",
  sample.hclust = "average",
  .sec.group = NULL,
  rmun = FALSE,
  rm.zero = TRUE,
  order.by.feature = FALSE,
  ...
)

## S4 method for signature 'grouped_df_mpse'
mp_plot_abundance(
  .data,
  .abundance = NULL,
  .group = NULL,
  taxa.class = NULL,
  topn = 10,
  relative = TRUE,
  force = FALSE,
  plot.group = FALSE,
  geom = "flowbar",
  feature.dist = "bray",
  feature.hclust = "average",
  sample.dist = "bray",
  sample.hclust = "average",
  .sec.group = NULL,
  rmun = FALSE,
  rm.zero = TRUE,
  order.by.feature = FALSE,
  ...
)

Arguments

.data	MPSE object or tbl_mpse object
.abundance	the column name of abundance to be plotted.
.group	the column name of group to be calculated and plotted, default is NULL.
taxa.class	name of taxonomy class, default is NULL, meaning the Phylum class will be plotted.
topn	integer the number of the top most abundant, default is 10.
relative	logical whether calculate the relative abundance and plotted.
force	logical whether calculate the relative abundance forcibly when the abundance is not be rarefied, default is FALSE.
plot.group	logical whether plotting the abundance of specified taxa.class taxonomy with group not sample level, default is FALSE.
geom	character which type plot, options is 'flowbar' 'bar' and 'heatmap', default is 'flowbar'.
feature.dist	character the method to calculate the distance between the features, based on the '.abundance' of 'taxa.class', default is 'bray', options refer to the 'distmethod' of [mp_cal_dist()] (except unifrac related).
feature.hclust	character the agglomeration method for the features, default is 'average', options are 'single', 'complete', 'average', 'ward.D', 'ward.D2', 'centroid' 'median' and 'mcquitty'.
sample.dist	character the method to calculate the distance between the samples based on the '.abundance' of 'taxa.class', default is 'bray', options refer to the 'distmethod' of [mp_cal_dist()] (except unifrac related).
sample.hclust	character the agglomeration method for the samples, default is 'average', options are 'single', 'complete', 'average', 'ward.D', 'ward.D2', 'centroid' 'median' and 'mcquitty'.
.sec.group	the column name of second group to be plotted with nested facet, default is NULL, this argument will be deprecated in the next version.
rmun	logical whether to group the unknown taxa to Others category, such as "g__un_xxx", default is FALSE, meaning do not group them to Others category.
rm.zero	logical whether to display the zero abundance, which only work with geom='heatmap' default is TRUE.
order.by.feature	character adjust the order of axis x, default is FALSE, if it is NULL or TRUE, meaning the order of axis.x will be visualizing with the order of samples by highest abundance of features.
...	additional parameters, when the geom = "flowbar", it can specify the parameters of 'geom_stratum' of 'ggalluvial', when the geom = 'bar', it can specify the parameters of 'geom_bar' of 'ggplot2', when the geom = "heatmap", it can specify the parameter of 'geom_tile' of 'ggplot2'.

Author(s)

Shuangbin Xu

Examples

## Not run: 
data(mouse.time.mpse)
mouse.time.mpse %<>%
  mp_rrarefy()
mouse.time.mpse
mouse.time.mpse %<>%
  mp_cal_abundance(.abundance=RareAbundance, action="add") %>%
  mp_cal_abundance(.abundance=RareAbundance, .group=time, action="add")
mouse.time.mpse
p1 <- mouse.time.mpse %>%
      mp_plot_abundance(.abundance=RelRareAbundanceBySample, 
                        .group=time, 
                        taxa.class="Phylum", 
                        topn=20)
p2 <- mouse.time.mpse %>%
      mp_plot_abundance(.abundance = Abundance,
                        taxa.class = Phylum,
                        topn = 20,
                        relative = FALSE,
                        force = TRUE
                       )
p3 <- mouse.time.mpse %>%
      mp_plot_abundance(.abundance = RareAbundance, 
                        .group = time,
                        taxa.class = Phylum, 
                        topn = 20,
                        relative = FALSE,
                        force = TRUE
                        )
p4 <- mouse.time.mpse %>%
      mp_plot_abundance(.abundance = RareAbundance,
                        .group = time,
                        taxa.class = Phylum,
                        topn = 20,
                        relative = FALSE,
                        force = TRUE,
                        plot.group = TRUE
                        )

## End(Not run)

xiangpin/MicrobitaProcess documentation built on Nov. 6, 2024, 1:15 a.m.