Last chance! 50% off unlimited learning
Sale ends in
biom-class
.biom-class
, represented as a
data.frame
(if possible) or a list, with
proper index names.
observation_metadata(x, rows, parallel=FALSE)
biom-class
.numeric-class
) or index names
(character-class
).plyr-package
via the
foreach-package
.data.frame
or list
containing the meta data, with index names. The precise
form of the object returned depends on the metadata
stored in x
. A data.frame
is created if
possible.
min_dense_file = system.file("extdata", "min_dense_otu_table.biom", package = "biom")
min_sparse_file = system.file("extdata", "min_sparse_otu_table.biom", package = "biom")
rich_dense_file = system.file("extdata", "rich_dense_otu_table.biom", package = "biom")
rich_sparse_file = system.file("extdata", "rich_sparse_otu_table.biom", package = "biom")
min_dense_file = system.file("extdata", "min_dense_otu_table.biom", package = "biom")
rich_dense_char = system.file("extdata", "rich_dense_char.biom", package = "biom")
rich_sparse_char = system.file("extdata", "rich_sparse_char.biom", package = "biom")
# Read the biom-format files
x1 = read_biom(min_dense_file)
x2 = read_biom(min_sparse_file)
x3 = read_biom(rich_dense_file)
x4 = read_biom(rich_sparse_file)
x5 = read_biom(rich_dense_char)
x6 = read_biom(rich_sparse_char)
# Extract metadata
observation_metadata(x1)
observation_metadata(x2)
observation_metadata(x3)
observation_metadata(x3, 2:4)
observation_metadata(x3, 2)
observation_metadata(x3, c("GG_OTU_3", "GG_OTU_4", "whoops"))
observation_metadata(x4)
observation_metadata(x5)
observation_metadata(x6)
Run the code above in your browser using DataLab