rsearch_obj: Create Rsearch object

Description

rsearch_obj standardizes and organizes data into an Rsearch object. An Rsearch object is a list containing three elements with data structures that can be used as input to build a phyloseq object in the phyloseq package.

Usage

rsearch_obj(
  readcount_data,
  sequence_data,
  sample_data,
  sample_id_col = "sample_id"
)

Value

A straightforward named list with three elements:

readcount.mat: A numeric matrix of OTU abundances with OTUs as rows and samples as columns.
sequence.df: A data.frame with one row for each OTU sequence and
sampledata.df: A data frame containing data about the samples.

Arguments

readcount_data: (Required). A file path or a data frame (or tibble) containing OTU count data, typically the output from vs_cluster_size or similar. This must have one row per OTU and one column per sample. The first column must contain OTU identifiers corresponding to those in the first column of sequence_data, and the remaining columns must have names matching the sample identifiers in sample_data. OTUs and samples not found across all data structures are discarded.
sequence_data: (Required). A file path or a data frame (or tibble) containing centroid sequences representing each OTU, typically obtained from clustering (vs_cluster_size) or denoising (vs_cluster_unoise). The first column must be called Header and contain OTU identifiers. One of the remaining columns must be named Sequence, containing the actual DNA sequences. Additional columns may include taxonomic classification data, e.g. from vs_sintax.
sample_data: (Required). A file path or a data frame (or tibble) containing metadata about each sample. Samples are assumed to be in rows, and one of the columns must contain a unique identifier for each sample that matches the column names in readcount_data.
sample_id_col: (Optional). A character string specifying the name of the column in sample_data that contains the unique sample identifiers. This column will be used to match sample metadata to read count data. Defaults to "sample_id".

Details

This function standardizes and organizes data into an Rsearch object: a structured three key data components used or generated during the Rsearch workflow: read count data, sequence data, and sample data.

The function accepts three datasets—read count data, sequence data, and sample metadata, and returns a streamlined input suitable for constructing a phyloseq object using the rsearch2phyloseq function. The implementation uses a standard list in R rather than a specialized class providing an open and easily accessible structure.

To convert this object into a phyloseq object, use rsearch2phyloseq.

Examples

Run this code

# Define inputs
readcount.dta <- system.file("extdata/readcount_data.tsv", package = "Rsearch")
sequence.dta <- system.file("extdata/sequence_data.tsv", package = "Rsearch")
sample.dta <- system.file("extdata/sample_data.tsv", package = "Rsearch")

# Create Rsearch object
obj <- rsearch_obj(readcount_data = readcount.dta,
                   sequence_data = sequence.dta,
                   sample_data = sample.dta,
                   sample_id_col = "sample_id")

# Convert Rsearch object to phyloseq object
phy_obj <- rsearch2phyloseq(obj, sample_id_col = "sample_id")

# Convert phyloseq object to Rsearch object
rsearch_obj <- phyloseq2rsearch(phy_obj)