distmat_stats | R Documentation |
Run statistics on a distance matrix vs a categorical or numeric variable.
distmat_stats(dm, groups, test = "adonis2", seed = 0, permutations = 999)
dm |
A |
groups |
A named vector of grouping values. The names should
correspond to |
test |
Permutational test for accessing significance. Options are:
Default: |
seed |
Random seed for permutations. Default: |
permutations |
Number of random permutations to use.
Default: |
A data.frame with summary statistics from vegan::permustats()
.
The columns are:
.n - The size of the distance matrix.
.stat - The observed statistic. For mrpp, this is the overall weighted mean of group mean distances.
.z - The difference of observed statistic and mean of permutations divided by the standard deviation of permutations (also known as z-values). Evaluated from permuted values without observed statistic.
.p.val - Probability calculated by test
.
R commands for reproducing the results are in $code
.
Other beta_diversity:
bdiv_boxplot()
,
bdiv_corrplot()
,
bdiv_heatmap()
,
bdiv_ord_plot()
,
bdiv_ord_table()
,
bdiv_stats()
,
bdiv_table()
Other stats_tables:
adiv_stats()
,
bdiv_stats()
,
stats_table()
,
taxa_stats()
library(rbiom)
hmp10 <- hmp50$clone()
hmp10$counts <- hmp10$counts[,1:10]
dm <- bdiv_distmat(hmp10, 'unifrac')
distmat_stats(dm, groups = pull(hmp10, 'Body Site'))
distmat_stats(dm, groups = pull(hmp10, 'Age'))
# See the R code used to calculate these statistics:
stats <- distmat_stats(dm, groups = pull(hmp10, 'Age'))
stats$code
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