mp_cal_pcoa-methods: Principal Coordinate Analysis with MPSE or tbl_mpse object

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

Principal Coordinate Analysis with MPSE or tbl_mpse object

Description

Principal Coordinate Analysis with MPSE or tbl_mpse object

Usage

mp_cal_pcoa(
  .data,
  .abundance,
  distmethod = "bray",
  .dim = 3,
  action = "add",
  ...
)

## S4 method for signature 'MPSE'
mp_cal_pcoa(
  .data,
  .abundance,
  distmethod = "bray",
  .dim = 3,
  action = "add",
  ...
)

## S4 method for signature 'tbl_mpse'
mp_cal_pcoa(
  .data,
  .abundance,
  distmethod = "bray",
  .dim = 3,
  action = "add",
  ...
)

## S4 method for signature 'grouped_df_mpse'
mp_cal_pcoa(
  .data,
  .abundance,
  distmethod = "bray",
  .dim = 3,
  action = "add",
  ...
)

Arguments

.data	MPSE or tbl_mpse object
.abundance	the name of abundance to be calculated.
distmethod	character the method to calculate distance.
.dim	integer The number of dimensions to be returned, default is 3.
action	character "add" joins the pca result to the object and the 'pcoa' object also was add to the internal attributes of the object, "only" return a non-redundant tibble with the pca result. "get" return 'pcoa' object.
...	additional parameters see also 'mp_cal_dist'.

Value

update object or tbl according to the action.

Author(s)

Shuangbin Xu

Examples

data(mouse.time.mpse)
mpse <- mouse.time.mpse %>% 
        mp_decostand(.abundance=Abundance)
mpse
mpse %<>% mp_cal_pcoa(.abundance=hellinger, stmethod="bray", action="add")
library(ggplot2)
p <- mpse %>% mp_plot_ord(.ord=pcoa, .group=time, .color=time, ellipse=TRUE)
p <- p + 
     scale_fill_manual(values=c("#00AED7", "#009E73")) + 
     scale_color_manual(values=c("#00AED7", "#009E73"))  
## Not run: 
# Or run with action='only' and return tbl_df to visualize manual.
mouse.time.mpse %>% 
  mp_decostand(.abundance=Abundance) %>% 
  mp_cal_pcoa(.abundance=hellinger, distmethod="bray", .dim=2, action="only") -> tbl
tbl
x <- names(tbl)[grepl("PCo1 ", names(tbl))] %>% as.symbol()
y <- names(tbl)[grepl("PCo2 ", names(tbl))] %>% as.symbol()
library(ggplot2)
tbl %>% 
 ggplot(aes(x=!!x, y=!!y, color=time)) + 
 stat_ellipse(aes(fill=time), geom="polygon", alpha=0.5) +
 geom_point() +
 geom_vline(xintercept=0, color="grey20", linetype=2) + 
 geom_hline(yintercept=0, color="grey20", linetype=2) +
 theme_bw() +
 theme(panel.grid=element_blank())

## End(Not run)

xiangpin/MicrobiotaProcess documentation built on Nov. 12, 2024, 2:05 p.m.