RCbray1 | R Documentation |
Calculate RCbray-curtis
RCbray1(
otutab,
reps = 9,
threads = 1,
classic_metric = TRUE,
split_ties = TRUE
)
otutab |
otutab |
reps |
how many simulation performed? |
threads |
use how many threads to calculate (default:4) |
classic_metric |
standardizes the metric to range from -1 to 1 |
split_ties |
adds half of the number of null observations that are equal to the observed number of shared species to the calculation- this is highly recommended |
Parallelized version of the Raup-Crick algorithm for "abundance" data (Stegen et al. 2013).
a dist
if (requireNamespace("picante")) {
data(otutab, package = "pcutils")
df2tree(taxonomy) -> phylo
b_NTI1(phylo, otutab) -> bnti_res
RCbray1(otutab, reps = 9) -> rc_res
data.frame(
type = factor(c("Homo_S", "Heter_S", "Homo_D", "D_limit", "Undominated"),
levels = c("Homo_S", "Heter_S", "Homo_D", "D_limit", "Undominated")
),
number = c(
sum(bnti_res < (-2)), sum(bnti_res > 2),
sum((abs(bnti_res) < 2) & (abs(rc_res) < 0.95)),
sum((abs(bnti_res) < 2) & (rc_res < (-0.95))),
sum((abs(bnti_res) < 2) & (rc_res > 0.95))
)
) -> com_pro
pcutils::gghuan(com_pro, reorder = FALSE)
}
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