mp_anosim {MicrobiotaProcess} | 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)