Assign sequence abundances, sequence classifications, bins, bin representative sequences, bin classifications or treatments to a strollur object

Usage

assign(
  data,
  table,
  type = "bin",
  bin_type = "otu",
  table_names = list(sequence_name = "sequence_name", abundance = "abundance", sample =
    "sample", treatment = "treatment", taxonomy = "taxonomy", bin_name = "bin_name"),
  reference = NULL,
  verbose = TRUE
)

Arguments

data,

a strollur object

table,

a data.frame containing the data you wish to assign

type,

a string containing the type of data. Options include: 'sequence_abundance', 'sequence_taxonomy', 'bin', 'bin_representative', 'bin_taxonomy' and 'treatment'. Default = "bin".

bin_type,

string containing the bin type you would like the number of bins for. Default = "otu".

table_names,

named list used to indicate the names of the columns in the table. By default:

table_names <- list(sequence_name = "sequence_name", abundance = "abundance", sample = "sample", treatment = "treatment", taxonomy = "taxonomy", bin_name = "bin_name")

In table_names, 'sequence_name' is a string containing the name of the column in 'table' that contains the sequence names. Default column name is 'sequence_name'.

In table_names, 'abundance' is a string containing the name of the column in 'table' that contains the abundances. Default column name is 'abundance'.

In table_names, 'sample' is a string containing the name of the column in 'table' that contains the samples. Default column name is 'sample'.

In table_names, 'treatment' is a string containing the name of the column in 'table' that contains the treatment names. Default column name is 'treatment'.

In table_names, 'taxonomy' is a string containing the name of the column in 'table' that contains the classifications. Default column name is 'taxonomy'.

In table_names, 'bin_name' is a string containing the name of the column in 'table' that contains the bin names. Default column name is 'bin_name'.

reference,

a list created by the function [new_reference]. Optional.

verbose,

boolean indicating whether or not you want progress messages. Default = TRUE.

Value

an updated strollur object

Examples


# Assign sequence classifications

# create a new empty strollur object named 'example_dataset'
data <- new_dataset(dataset_name = "example_dataset")

sequence_classifications <- read_mothur_taxonomy(strollur_example(
  "final.taxonomy.gz"
))

assign(
  data,
  table = sequence_classifications, type = "sequence_taxonomy"
)
#> Assigned 2425 sequence taxonomies.

# Assigning bins

# read mothur's otu list file into data.frame
otu_data <- read_mothur_list(list = strollur_example(
  "final.opti_mcc.list.gz"
))

# read mothur's asv list file into data.frame
asv_data <- read_mothur_list(list = strollur_example(
  "final.asv.list.gz"
))

# read mothur's phylotype list file into data.frame
phylo_data <- read_mothur_list(list = strollur_example(
  "final.tx.list.gz"
))

# read otu bin representative sequences into a data.frame
bin_reps <- readRDS(strollur_example("miseq_representative_sequences.rds"))

# assign 'otu' bins using sequence names
assign(data, table = otu_data, bin_type = "otu")
#> Assigned 531 otu bins.

# assign 'asv' bins using sequence names
assign(data, table = asv_data, bin_type = "asv")
#> Assigned 2425 asv bins.

# assign 'phylotype' bins using sequence names
assign(data, table = phylo_data, bin_type = "phylotype")
#> Assigned 63 phylotype bins.

# assign 'otu' bin representative sequences
assign(data, table = bin_reps, type = "bin_representative")
#> Assigned 531 otu bin representative sequences.

# To assign abundance only bins

# create a new empty strollur object named 'example_dataset'
data <- new_dataset(dataset_name = "example_dataset")

# read mothur's shared file
otu_data <- read_mothur_shared(strollur_example("final.opti_mcc.shared"))

# assign abundance only otus parsed by sample
assign(data, table = otu_data, bin_type = "otu")
#> Assigned 531 otu bins.

# Assigning bin classifications

# read bin taxonomies
otu_data <- read_mothur_cons_taxonomy(strollur_example(
  "final.cons.taxonomy"
))

# assign otu consensus taxonomies
assign(
  data,
  table = otu_data,
  type = "bin_taxonomy", bin_type = "otu"
)
#> Assigned 531 otu bin taxonomies.

# Assign treatments

sample_assignments <- readRDS(strollur_example("miseq_sample_design.rds"))

assign(data, table = sample_assignments, type = "treatment")
#> Assigned 19 samples to treatments.