View source: R/beta_div_test.R
var_par_rarperm_pq | R Documentation |
This is an extension of the function var_par_pq()
. The main addition is
the computation of nperm permutations with rarefaction even depth by
sample. The return object
var_par_rarperm_pq(
physeq,
list_component,
dist_method = "bray",
nperm = 99,
quantile_prob = 0.975,
dbrda_computation = FALSE,
dbrda_signif_pval = 0.05,
sample.size = min(sample_sums(physeq)),
verbose = FALSE,
progress_bar = TRUE
)
physeq |
(required): a |
list_component |
(required) A named list of 2, 3 or four vectors with
names from the |
dist_method |
(default "bray") the distance used. See
|
nperm |
(int) The number of permutations to perform. |
quantile_prob |
(float, |
dbrda_computation |
(logical) Do dbrda computations are runned for each individual component (each name of the list component) ? |
dbrda_signif_pval |
(float, |
sample.size |
(int) A single integer value equal to the number of
reads being simulated, also known as the depth. See
|
verbose |
(logical). If TRUE, print additional informations. |
progress_bar |
(logical, default TRUE) Do we print progress during the calculation? |
This function is mainly a wrapper of the work of others.
Please make a reference to vegan::varpart()
if you
use this function.
A list of class varpart with additional information in the
$part$indfract
part. Adj.R.square is the mean across permutation.
Adj.R.squared_quantil_min and Adj.R.squared_quantil_max represent
the quantile values of adjuste R squared
Adrien Taudière
var_par_pq()
, vegan::varpart()
, plot_var_part_pq()
if (requireNamespace("vegan")) {
data_fungi_woNA <- subset_samples(data_fungi, !is.na(Time) & !is.na(Height))
res_var_9 <- var_par_rarperm_pq(
data_fungi_woNA,
list_component = list(
"Time" = c("Time"),
"Size" = c("Height", "Diameter")
),
nperm = 9,
dbrda_computation = TRUE
)
res_var_2 <- var_par_rarperm_pq(
data_fungi_woNA,
list_component = list(
"Time" = c("Time"),
"Size" = c("Height", "Diameter")
),
nperm = 2,
dbrda_computation = TRUE
)
}
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