Package 'rbiom'

Title: Read/Write, Transform, and Summarize 'BIOM' Data
Description: A toolkit for working with Biological Observation Matrix ('BIOM') files. Features include reading/writing all 'BIOM' formats, rarefaction, alpha diversity, beta diversity (including 'UniFrac'), summarizing counts by taxonomic level, and sample subsetting. Standalone functions for reading, writing, and subsetting phylogenetic trees are also provided. All CPU intensive operations are encoded in C with multi-thread support.
Authors: Daniel P. Smith [aut, cre, cph]
Maintainer: Daniel P. Smith <[email protected]>
License: AGPL-3
Version: 1.0.3
Built: 2024-08-16 06:37:47 UTC
Source: CRAN

Help Index

Estimate the diversity of each sample.

Description

Estimate the diversity of each sample.

Usage

alpha.div(biom, rarefy = FALSE)

Arguments

biom

A matrix, simple_triplet_matrix, or BIOM object, as returned from read.biom. For matrices, the rows and columns are assumed to be the taxa and samples, respectively.
rarefy

Control how/whether rarefactions are done prior to alpha diversity computations. Options are:

FALSE

Use each sample's current set of observations without applying any rarefaction. (Default)

TRUE

Automatically select and apply a single rarefaction.

"multi"

Automatically select and apply multiple rarefactions.

integer vector

Rarefy at the specified depth(s).

Value

A data frame of four diversity values for each sample in biom. The column names are Sample, Depth and the diversity metrics: OTUs, Shannon, Chao1, Simpson, and InvSimpson. The row names are the sample names, except when multiple rarefactions are done.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    ad <- alpha.div(biom)
    head(ad)
    
    biom <- subset(biom, `Body Site` == "Saliva" & Age < 26)
    ad   <- alpha.div(biom, "multi")
    boxplot(Shannon ~ Depth, data=ad, xlab="Reads", ylab="Diversity")

Make a distance matrix of samples vs samples.

Description

Make a distance matrix of samples vs samples.

Usage

beta.div(biom, method, weighted = TRUE, tree = NULL)

Arguments

biom

A matrix, simple_triplet_matrix, or BIOM object, as returned from read.biom. For matrices, the rows and columns are assumed to be the taxa and samples, respectively.
method

The distance algorithm to use. Options are: “manhattan”, “euclidean”, “bray-curtis”, “jaccard”, and “unifrac”. Non-ambiguous abbrevations of the method names are also accepted. A phylogentic tree must be present in biom or explicitly provided via tree= to use the UniFrac methods.
weighted

Take relative abundances into account. When weighted=FALSE, only presence/absence is considered.
tree

A phylo object representing the phylogenetic relationships of the taxa in biom. Will be taken from the tree embedded in the biom object if not explicitly specified. Only required for computing UniFrac distance matrices.

Value

A distance matrix.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    biom <- select(biom, 1:10)
    
    dm <- beta.div(biom, 'unifrac')
    
    as.matrix(dm)[1:4,1:4]
    plot(hclust(dm))

Get the abundance counts.

Description

Get the abundance counts.

Usage

counts(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A numeric matrix of the sample abundance counts in biom.

See Also

Other accessor functions: info(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    counts(biom)[1:4,1:5]

Get biom's misc information.

Description

Get biom's misc information.

Usage

info(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A data frame of the metadata in biom.

See Also

Other accessor functions: counts(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    info(biom)

Get the sample metadata.

Description

Get the sample metadata.

Usage

metadata(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A data frame of the metadata in biom.

See Also

Other accessor functions: counts(), info(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    metadata(biom)[1:4,1:3]

Number of samples in a BIOM.

Description

Number of samples in a BIOM.

Usage

nsamples(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

The number of samples present.

See Also

Other accessor functions: counts(), info(), metadata(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    nsamples(biom)

Number of taxa in a BIOM.

Description

Number of taxa in a BIOM.

Usage

ntaxa(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

The number of taxa present.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    ntaxa(biom)

Get the phylogenetic tree.

Description

Get the phylogenetic tree.

Usage

phylogeny(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A phylo class object of the tree in biom.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), sample.names(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    summary(phylogeny(biom))

Summarize the contents of a BIOM object

Description

Summarize the contents of a BIOM object

Usage

## S3 method for class 'BIOM'
print(x, ...)

Arguments

x

A BIOM object, as returned from read.biom.
...

Not used.

Value

NULL (invisibly)

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    print(biom)

Subset counts so that all samples have the same number of observations.

Description

Subset counts so that all samples have the same number of observations.

Usage

rarefy(biom, depth = NULL, seed = 0)

Arguments

biom

A matrix, simple_triplet_matrix, or BIOM object, as returned from read.biom. For matrices, the rows and columns are assumed to be the taxa and samples, respectively.
depth

The number of observations to keep, per sample. If set to NULL, a depth will be automatically selected. Samples that have fewer than this number of observations will be dropped. If called on data with non-integer abundances, values will be re-scaled to integers between 1 and depth such that they sum to depth.
seed

An integer to use for seeding the random number generator. If you need to create different random rarefactions of the same BIOM object, set this seed value to a different number each time.

Value

A matrix, simple_triplet_matrix, or BIOM object, depending on the input object type. The type of object provided is the same type that is returned. The retained observations are randomly selected, based on a seed value derived from the BIOM object. Therefore, rarefying the same biom to the same depth will always produce the same resultant rarification.

Examples

library(rbiom)

    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    range(slam::col_sums(biom$counts))

    biom <- rarefy(biom, depth=1000)
    range(slam::col_sums(biom$counts))

rbiom: Read/Write, Transform, and Summarize BIOM Data

Description

A toolkit for working with Biological Observation Matrix (BIOM) files. Features include reading/writing all BIOM formats, rarefaction, alpha diversity, beta diversity (including UniFrac), summarizing counts by taxonomic level, and sample subsetting. Standalone functions for reading, writing, and subsetting phylogenetic trees are also provided. All CPU intensive operations are encoded in C with multi-thread support.

Multithreading

Many rbiom functions support multithreading:

The default behavior of these function is to run on as many cores as are available in the local compute environment. If you wish to limit the number of simultaneous threads, set RcppParallel's numThreads option. For instance: 

    RcppParallel::setThreadOptions(numThreads = 4)

Extracts counts, metadata, taxonomy, and phylogeny from a biom file.

Description

Extracts counts, metadata, taxonomy, and phylogeny from a biom file.

Usage

read.biom(src, tree = "auto", prune = FALSE)

Arguments

src

Input data as either a file path, URL, or JSON string. read.biom can read BIOM files formatted according to both the version 1.0 (JSON) and 2.1 (HDF5) specifications as well as classical tabular format. URLs must begin with http://, https://, ftp://, or ftps://. JSON files must have { as their first non-whitespace character. Compressed (gzip or bzip2) BIOM files are also supported. NOTE: to read HDF5 formatted BIOM files, the BioConductor R package rhdf5 must be installed.
tree

The default value of auto will read the tree from the BIOM file specified in src, if present. The value TRUE will do the same, but will generate an error message if a tree is not present. Setting tree=FALSE will return a BIOM object without any tree data. You may also provide a file path, URL, or Newick string to load that tree data into the final BIOM object.
prune

Should samples and taxa with zero observations be discarded?

Value

A BIOM class object containing the parsed data. This object can be treated as a list with the following named elements:

counts

A numeric slam sparse matrix of observation counts. Taxa (OTUs) as rows and samples as columns.

metadata

A data frame containing any embedded metadata. Row names are sample IDs.

taxonomy

Character matrix of taxonomic names, if given. Row names are taxa (OTU) IDs. Column rows are named Kingdom, Phylum, Class, Order, Family, Genus, Species, and Strain, or TaxLvl.1, TaxLvl.2, ... , TaxLvl.N when more than 8 levels of taxonomy are encoded in the biom file.

phylogeny

An object of class phylo defining the phylogenetic relationships between the taxa. Although the official specification for BIOM only includes phylogenetic trees in BIOM version 2.1, if a BIOM version 1.0 file includes a phylogeny entry with newick data, then it will be loaded here as well. The ape package has additional functions for working with phylo objects.

sequences

A named character vector, where the names are taxonomic identifiers and the values are the sequences they represent. These values are not part of the official BIOM specification, but will be read and written when defined.

info

A list of other attributes defined in the BIOM file, such as id, type, format, format_url, generated_by, date, matrix_type, matrix_element_type, Comment, and shape

metadata, taxonomy, and phylogeny are optional components of the BIOM file specification and therefore will be empty in the returned object when they are not provided by the BIOM file.

Examples

library(rbiom)

    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)

    summary(biom)

    # Taxa Abundances
    as.matrix(biom$counts[1:4,1:4])

    top5 <- names(head(rev(sort(slam::row_sums(biom$counts))), 5))
    biom$taxonomy[top5,c('Family', 'Genus')]
    as.matrix(biom$counts[top5, 1:6])

    # Metadata
    table(biom$metadata$Sex, biom$metadata$`Body Site`)
    sprintf("Mean age: %.1f", mean(biom$metadata$Age))

    # Phylogenetic tree
    tree <- biom$phylogeny
    top5.tree <- rbiom::subtree(tree, top5)
    ape::plot.phylo(top5.tree)

Parse a fasta file into a named character vector.

Description

Parse a fasta file into a named character vector.

Usage

read.fasta(file, ids = NULL)

Arguments

file

A file with fasta-formatted sequences. Can optionally be compressed with gzip, bzip2, xz, or lzma.
ids

Character vector of IDs to retrieve. The default, NULL, will retrieve everything.

Value

A named character vector in which names are the fasta headers and values are the sequences.

Read a newick formatted phylogenetic tree.

Description

A phylogenetic tree is required for computing UniFrac distance matrices. You can load a tree either from a file or by providing the tree string directly. This tree must be in Newick format, also known as parenthetic format and New Hampshire format.

Usage

read.tree(src)

Arguments

src

Input data as either a file path, URL, or Newick string. URLs must begin with http://, https://, ftp://, or ftps://. Newick strings must have ( as their first non-whitespace character. Compressed (gzip or bzip2) Newick files are also supported.

Value

A phylo class object representing the tree.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "newick.tre", package = "rbiom")
    tree <- read.tree(infile)
    
    tree <- read.tree("
        (t9:0.99,((t5:0.87,t2:0.89):0.51,(((t10:0.16,(t7:0.83,t4:0.96)
        :0.94):0.69,(t6:0.92,(t3:0.62,t1:0.85):0.54):0.23):0.74,t8:0.1
        2):0.43):0.67);")

Get the sample names.

Description

Get the sample names.

Usage

sample.names(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A character vector of the sample IDs / names in biom.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), phylogeny(), sequences(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    sample.names(biom)

Reduce samples to a specific list

Description

Reduce samples to a specific list

Usage

select(biom, samples = NULL, nTop = NULL, nRandom = NULL, seed = 0)

Arguments

biom

A BIOM object, as returned from read.biom.
samples

Sample names, indices, or a logical vector identifying the samples to keep. The latter two should be based on the order of sample names given by colnames(biom$counts).
nTop

Selects this number of samples, taking the sample with the most observations first, then the sample with the second-most observations, etc. If nTop is higher than the number of samples in the dataset, the entire dataset will be returned. See note.
nRandom

Randomly selects this number of samples. If higher than the number of samples in the dataset, the entire dataset will be returned. See note.
seed

Random seed, used when selecting nRandom samples.

Note: Generally, you will specify only one of the filters: samples, nTop, or nRandom. However, specifying multiple filters is allowed; they will be applied in the order listed above.

Value

A BIOM object.

See Also

subset

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    ex1 <- select(biom, c('HMP14', 'HMP22', 'HMP03'))
    ex2 <- select(biom, c(32, 11, 28, 16, 46, 5))
    ex3 <- select(biom, 1:50 %% 6 == 0)
    ex4 <- select(biom, nRandom = 10)
    ex5 <- select(biom, nTop = 5)
    ex6 <- select(biom, samples = 10:40, nTop = 20, nRandom = 10)

DNA sequence associated with each taxonomic identifier.

Description

DNA sequence associated with each taxonomic identifier.

Usage

sequences(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A named character vector of sequences in biom. If this data is not present, then returns NULL.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), taxa.names(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    sequences(biom)[1:4]
    
    # Write to a compressed fasta file in the temporary directory:
    seqs <- sequences(biom)
    conn <- bzfile(file.path(tempdir(), "Sequences.fa.bz2"), "w")
    cat(sprintf(">%s\n%s", names(seqs), seqs), file=conn, sep="\n")
    close(conn)
    
    # You can also use the write.fasta function for this task:
    write.fasta(biom, file.path(tempdir(), "Sequences.fa.gz"))

Subset samples using the BIOM object's metadata

Description

Subset samples using the BIOM object's metadata

Usage

## S3 method for class 'BIOM'
subset(x, ...)

Arguments

x

A BIOM object, as returned from read.biom.
...

Test to run on the metadata to identify samples to retain.

Value

A BIOM object.

See Also

select

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    ex1 <- subset(biom, Age > 30)
    ex2 <- subset(biom, `Body Site` %in% c("Saliva", "Stool"))
    ex3 <- subset(biom, Age < 25 & BMI > 22)

Create a subtree by specifying tips to keep.

Description

Create a subtree by specifying tips to keep.

Usage

subtree(tree, tips)

Arguments

tree

A phylo object, as returned from read.tree.
tips

A character, numeric, or logical vector of tips to keep.

Value

A phylo object for the subtree.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "newick.tre", package = "rbiom")
    tree <- read.tree(infile)
    
    leafs   <- tips(tree)
    subtree <- subtree(tree, head(leafs))

Get the taxa names.

Description

Get the taxa names.

Usage

taxa.names(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A character vector of the taxa IDs / names in biom.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.ranks(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    taxa.names(biom) %>% head()

Get the taxa ranks.

Description

Get the taxa ranks.

Usage

taxa.ranks(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A character vector of the taxa ranks in biom.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxonomy()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    taxa.ranks(biom)

Generate a matrix of samples by taxa, at the specified taxonomic rank.

Description

Generate a matrix of samples by taxa, at the specified taxonomic rank.

Usage

taxa.rollup(biom, rank = "OTU", map = NULL, lineage = FALSE, sparse = FALSE)

Arguments

biom

A matrix, simple_triplet_matrix, or BIOM object, as returned from read.biom. For matrices, the rows and columns are assumed to be the taxa and samples, respectively.
rank

The taxonomic rank. E.g. “OTU”, “Phylum”, etc. May also be given numerically: 0 for OTU, 1 for the highest level (i.e. Kingdom), and extending to the number of taxonomic ranks encoded in the original biom file. See example below to fetch the names of all available ranks.
map

A character matrix defining the value that each taxa IDs is assigned for each taxonomic rank. If map=NULL and biom is a BIOM class object, the map will be automatically loaded from biom$taxonomy. map must not be null when biom is a matrix or simple_triplet_matrix. See the example below for an example of map's structure.
lineage

Include all ranks in the name of the taxa. For instance, setting to TRUE will produce Bacteria; Actinobacteria; Coriobacteriia; Coriobacteriales. Whereas setting to FALSE (the default) will return simply Coriobacteriales. You want to set this to TRUE if you have genus names (such as Incertae_Sedis) that map to multiple higher level ranks.
sparse

If true, returns a sparse matrix as described by slam::simple_triplet_matrix, otherwise returns a normal R matrix object. Sparse matrices will likely be considerably more memory efficient in this scenario.

Value

A numeric matrix with samples as column names, and taxonomic identifiers as row names.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    colnames(biom$taxonomy)
    
    phyla <- taxa.rollup(biom, 'Phylum')
    phyla[1:4,1:6]
    
    # Custom matrices should be formatted like so:
    counts <- as.matrix(biom$counts)
    map    <- biom$taxonomy
    
    counts[1:3,1:6]
    map[1:3,1:4]
    
    phyla <- taxa.rollup(counts, 'Phylum', map=map)
    phyla[1:3,1:6]

Get the taxonomy table.

Description

Get the taxonomy table.

Usage

taxonomy(biom)

Arguments

biom

A BIOM object, as returned from read.biom.

Value

A character matrix of the named taxonomies in biom.

See Also

Other accessor functions: counts(), info(), metadata(), nsamples(), ntaxa(), phylogeny(), sample.names(), sequences(), taxa.names(), taxa.ranks()

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    
    taxonomy(biom)[1:4,]

Names of a phylogenetic tree's tips/leafs.

Description

Names of a phylogenetic tree's tips/leafs.

Usage

tips(x)

Arguments

x

A phylo object, as returned from read.tree..

Value

A character vector with the leaf names.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "newick.tre", package = "rbiom")
    tree <- read.tree(infile)
    
    leafs   <- tips(tree)
    subtree <- subtree(tree, head(leafs))

Compute Weighted and Unweighted UniFrac distance matrices.

Description

This is the function called internally by beta.div, but is made visible here so you can use it with matrices and trees without having to first convert them to BIOM objects.

Usage

unifrac(biom, weighted = TRUE, tree = NULL)

Arguments

biom

A matrix, simple_triplet_matrix, or BIOM object, as returned from read.biom. For matrices, the rows and columns are assumed to be the taxa and samples, respectively.
weighted

Use weighted UniFrac, which takes abundance into account rather than simply presence/absence.
tree

A phylo object providing a phylogenetic tree for the taxa names in biom. If tree=NULL, then the tree will be loaded from biom, if encoded there.

Value

A distance matrix of class dist.

Examples

library(rbiom)
    
    infile <- system.file("extdata", "hmp50.bz2", package = "rbiom")
    biom <- read.biom(infile)
    biom <- select(biom, 1:10)
    
    dm <- unifrac(biom)
    plot(hclust(dm), cex=.8)
    as.matrix(dm)[1:4,1:4]
    
    # Using a custom matrix and tree
    mtx <- matrix(sample.int(12*20), ncol=20)
    dimnames(mtx) <- list(LETTERS[1:12], letters[1:20])
    tree <- ape::as.phylo(hclust(dist(mtx)))
    
    dm <- unifrac(mtx, tree=tree)
    as.matrix(dm)[1:4,1:4]

Write counts, metadata, taxonomy, and phylogeny to a biom file.

Description

Write counts, metadata, taxonomy, and phylogeny to a biom file.

Usage

write.biom(biom, file, format = "json")

Arguments

biom

The BIOM object to save to the file.
file

Path to the output file.
format

Options are “tab”, “json”, and “hdf5”, corresponding to classic tabular format, biom format version 1.0 and biom version 2.1, respectively. Abbreviations are also accepted. See http://biom-format.org/documentation/ for details. NOTE: to write HDF5 formatted BIOM files, the BioConductor R package rhdf5 must be installed.

Value

On success, returns NULL invisibly.

Write sequences from a BIOM object to a file in fasta format.

Description

Write sequences from a BIOM object to a file in fasta format.

Usage

write.fasta(seqs, outfile)

Arguments

seqs

A named character vector where names are sequence names and values are the sequences. Also accepts a BIOM object which contains sequences.
outfile

Path to the output fasta file. Files ending in .gz or .bz2 will be compressed accordingly.

Value

On success, returns NULL invisibly.

Write a newick formatted phylogenetic tree.

Description

Write a newick formatted phylogenetic tree.

Usage

write.tree(tree = NULL, file = NULL)

Arguments

tree

A phylo object, as returned from read.tree. Also accepts a BIOM object if it has a phylogentic tree.
file

Filename or connection to write the newick file to (optional).

Value

If file is NULL, the newick string as a character vector. Otherwise, the return value from writeChar, typically invsible(NULL).

Examples

library(rbiom)
    
    infile <- system.file("extdata", "newick.tre", package = "rbiom")
    tree   <- read.tree(infile)
    newick <- write.tree(tree)

Write data and summary information to a Microsoft Excel-compatible workbook.

Description

Write data and summary information to a Microsoft Excel-compatible workbook.

Usage

write.xlsx(biom, outfile, depth = NULL, seed = 0)

Arguments

biom

The BIOM object to save to the file.
outfile

Path to the output xlsx file.
depth

Depth to rarefy to. See rarefy function for details. Only use depth with BIOM files of type 'OTU table' and integer count values.
seed

Random seed to use in rarefying. See rarefy function for details.

Value

On success, returns NULL invisibly.

Note

Any data frame attributes on biom will be included as separate worksheets. An attribute named 'Reads Per Step' is treated specially and merged with the usual 'Reads Per Sample' tab - if provided, its row names should match those in biom exactly.