mp_envfit {MicrobiotaProcess} | R Documentation |
Fits an Environmental Vector or Factor onto an Ordination With MPSE or tbl_mpse Object
mp_envfit( .data, .ord, .env, .dim = 3, action = "only", permutations = 999, seed = 123, ... ) ## S4 method for signature 'MPSE' mp_envfit( .data, .ord, .env, .dim = 3, action = "only", permutations = 999, seed = 123, ... ) ## S4 method for signature 'tbl_mpse' mp_envfit( .data, .ord, .env, .dim = 3, action = "only", permutations = 999, seed = 123, ... ) ## S4 method for signature 'grouped_df_mpse' mp_envfit( .data, .ord, .env, .dim = 3, action = "only", permutations = 999, seed = 123, ... )
.data |
MPSE or tbl_mpse object |
.ord |
a name of ordination, option it is DCA, NMDS, RDA, CCA. |
.env |
the names of columns of sample group or environment information. |
.dim |
integer The number of dimensions to be returned, default is 3. |
action |
character "add" joins the envfit result to internal attributes of the object, "only" return a non-redundant tibble with the envfit result. "get" return 'envfit' 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 analysis reproducible, default is 123. |
... |
additional parameters see also 'vegan::envfit' |
update object according action
Shuangbin Xu
library(vegan) data(varespec, varechem) mpse <- MPSE(assays=list(Abundance=t(varespec)), colData=varechem) envformula <- paste("~", paste(colnames(varechem), collapse="+")) %>% as.formula mpse %<>% mp_cal_cca(.abundance=Abundance, .formula=envformula, action="add") mpse2 <- mpse %>% mp_envfit(.ord=cca, .env=colnames(varechem), permutations=9999, action="add") mpse2 %>% mp_plot_ord(.ord=cca, .group=Al, .size=Mn, show.shample=TRUE, show.envfit=TRUE) ## Not run: tbl <- mpse %>% mp_envfit(.ord=CCA, .env=colnames(varechem), permutations=9999, action="only") tbl library(ggplot2) library(ggrepel) x <- names(tbl)[grepl("^CCA1 ", names(tbl))] %>% as.symbol() y <- names(tbl)[grepl("^CCA2 ", names(tbl))] %>% as.symbol() p <- tbl %>% ggplot(aes(x=!!x, y=!!y)) + geom_point(aes(color=Al, size=Mn)) + geom_segment(data=dr_extract( name="CCA_ENVFIT_tb", .f=td_filter(pvals<=0.05 & label!="Humdepth") ), aes(x=0, y=0, xend=CCA1, yend=CCA2), arrow=arrow(length = unit(0.02, "npc")) ) + geom_text_repel(data=dr_extract( name="CCA_ENVFIT_tb", .f=td_filter(pvals<=0.05 & label!="Humdepth") ), aes(x=CCA1, y=CCA2, label=label) ) + geom_vline(xintercept=0, color="grey20", linetype=2) + geom_hline(yintercept=0, color="grey20", linetype=2) + theme_bw() + theme(panel.grid=element_blank()) p ## End(Not run)