mp_anosim | R Documentation |
Analysis of Similarities (ANOSIM) with MPSE or tbl_mpse object
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,
...
)
.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. |
update object according action argument
Shuangbin Xu
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)
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