mp_anosim-methods: Analysis of Similarities (ANOSIM) with MPSE or tbl_mpse...

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

Analysis of Similarities (ANOSIM) with MPSE or tbl_mpse object

Description

Analysis of Similarities (ANOSIM) with MPSE or tbl_mpse object

Usage

mp_anosim(
  .data,
  .abundance,
  .group,
  distmethod = "bray",
  action = "add",
  permutations = 999,
  seed = 123,
  ...
)

## S4 method for signature 'MPSE'
mp_anosim(
  .data,
  .abundance,
  .group,
  distmethod = "bray",
  action = "add",
  permutations = 999,
  seed = 123,
  ...
)

## S4 method for signature 'tbl_mpse'
mp_anosim(
  .data,
  .abundance,
  .group,
  distmethod = "bray",
  action = "add",
  permutations = 999,
  seed = 123,
  ...
)

## S4 method for signature 'grouped_df_mpse'
mp_anosim(
  .data,
  .abundance,
  .group,
  distmethod = "bray",
  action = "add",
  permutations = 999,
  seed = 123,
  ...
)

Arguments

.data	MPSE or tbl_mpse object
.abundance	the name of abundance to be calculated.
.group	The name of the column of the sample group information.
distmethod	character the method to calculate pairwise distances, default is 'bray'.
action	character "add" joins the ANOSIM result to internal attribute of the object, "only" and "get" return 'anosim' object can be analyzed using the related vegan funtion.
permutations	the number of permutations required, default is 999.
seed	a random seed to make the ANOSIM analysis reproducible, default is 123.
...	additional parameters see also 'anosim' of vegan.

Value

update object according action argument

Author(s)

Shuangbin Xu

Examples

data(mouse.time.mpse)
mouse.time.mpse %<>%
  mp_decostand(.abundance=Abundance)
# action = "get" will return a anosim object
mouse.time.mpse %>% 
  mp_anosim(.abundance=hellinger, .group=time, action="get")
# action = "only" will return a tbl_df that can be as the input of ggplot2.
library(ggplot2)
tbl <- mouse.time.mpse %>% 
       mp_anosim(.abundance=hellinger, 
                 .group=time,
                 permutations=999, # for more robust, set it to 9999
                 action="only")
tbl
tbl %>%
ggplot(aes(x=class, y=rank, fill=class)) + 
geom_boxplot(notch=TRUE, varwidth = TRUE)

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