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

Usage

assign(
  data,
  table,
  type = "bin",
  bin_type = "otu",
  table_names = list(sequence_name = "sequence_name", quality_score = "quality_score",
    abundance = "abundance", sample = "sample", treatment = "treatment", taxonomy =
    "taxonomy", level = "level", confidence = "confidence", 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, quality, bin_representative, bin_taxonomy, sample_distance 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", quality_score = "quality_score", abundance = "abundance", sample = "sample", treatment = "treatment", taxonomy = "taxonomy", level = "level", confidence = "confidence", 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, quality_score is a string containing the name of the column in 'table' that contains the sequence quality scores. It is used when you are adding quality data. Default column name is 'quality_score'.

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, level is a string containing the name of the column in the data.frame that contains the classifications. Default column name is level.

In table_names, confidence is a string containing the name of the column in the data.frame that contains the classifications confidence scores. Default column name is confidence.

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 <- strollur::new_dataset(dataset_name = "example_dataset")

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

strollur::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 <- strollur::read_mothur_list(list = strollur_example(
  "final.opti_mcc.list.gz"
))

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

# read mothur's phylotype list file into data.frame
phylo_data <- strollur::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
strollur::assign(data, table = otu_data, bin_type = "otu")
#> Assigned 531 otu bins.

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

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

# assign 'otu' bin representative sequences
strollur::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 <- strollur::new_dataset(dataset_name = "example_dataset")

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

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

# Assigning bin classifications

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

# assign otu consensus taxonomies
strollur::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"))

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

# Assign sample distances

dist_file <- strollur_example("final.opti_mcc.jclass.0.03.column.dist")
sample_dists <- readr::read_table(dist_file,
  col_names = FALSE,
  show_col_types = FALSE
)
strollur::assign(data, table = sample_dists, type = "sample_distance")
#> Assigned 171 samples distances.

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

Usage

Arguments

Value

See also

Examples