alpha.div(biom, rarefy = FALSE)beta.div(
biom,
method = "Bray-Curtis",
weighted = TRUE,
tree = NULL,
long = FALSE,
md = FALSE
)
counts(biom)
info(biom)
metadata(biom, field = NULL, cleanup = FALSE)
nsamples(biom)
ntaxa(biom)
phylogeny(biom)
read.biom(src, tree = "auto", prune = FALSE)
read.fasta(file, ids = NULL)
read.tree(src)
sample.names(biom)
# S3 method for rbiom
select(
.data,
samples = NULL,
nTop = NULL,
nRandom = NULL,
seed = 0,
biom = NULL,
...
)
sequences(biom)
subtree(tree, tips)
taxa.names(biom)
taxa.ranks(biom)
taxa.rollup(
biom,
rank = "OTU",
map = NULL,
lineage = FALSE,
sparse = FALSE,
taxa = NULL,
long = FALSE,
md = FALSE
)
taxonomy(biom, ranks = NULL, unc = "asis")
tips(x)
unifrac(biom, weighted = TRUE, tree = NULL)
write.biom(biom, file, format = "json")
write.fasta(seqs, outfile = NULL)
write.tree(tree, file = NULL)
write.xlsx(biom, outfile, depth = 0.1, seed = 0)
as.percent(biom)
comments(biom)
depth(biom)
depths_barplot(
biom,
rline = TRUE,
counts = TRUE,
labels = TRUE,
transform = "log10",
...
)
has.phylogeny(biom)
has.sequences(biom)
id(biom)
is.rarefied(biom)
repair(biom)
sample_subset(x, ...)
sample.sums(biom, long = FALSE, md = FALSE)
taxa_max(biom, rank = -1, lineage = FALSE, unc = "singly")
taxa.means(biom, rank = NULL)
taxa.sums(biom, rank = NULL)
top.taxa(biom, rank = "OTU", n = Inf)
top_taxa(biom, rank = "OTU", n = Inf)
comments(x) <- value
counts(x) <- value
id(x) <- value
metadata(x) <- value
phylogeny(x) <- value
sample.names(x) <- value
sequences(x) <- value
taxa.names(x) <- value
taxa.ranks(x) <- value
taxonomy(x) <- value