metacoder (version 0.3.7)

rarefy_obs: Calculate rarefied observation counts

Description

For a given table in a taxmap object, rarefy counts to a constant total. This is a wrapper around rrarefy that automatically detects which columns are numeric and handles the reformatting needed to use tibbles.

Usage

rarefy_obs(
  obj,
  data,
  sample_size = NULL,
  cols = NULL,
  other_cols = FALSE,
  out_names = NULL,
  dataset = NULL
)

Value

A tibble

Arguments

obj

A taxmap object

data

The name of a table in obj$data.

sample_size

The sample size counts will be rarefied to. This can be either a single integer or a vector of integers of equal length to the number of columns.

cols

The columns in data to use. By default, all numeric columns are used. Takes one of the following inputs:

TRUE/FALSE:

All/No columns will used.

Character vector:

The names of columns to use

Numeric vector:

The indexes of columns to use

Vector of TRUE/FALSE of length equal to the number of columns:

Use the columns corresponding to TRUE values.

other_cols

Preserve in the output non-target columns present in the input data. New columns will always be on the end. The "taxon_id" column will be preserved in the front. Takes one of the following inputs:

NULL:

No columns will be added back, not even the taxon id column.

TRUE/FALSE:

All/None of the non-target columns will be preserved.

Character vector:

The names of columns to preserve

Numeric vector:

The indexes of columns to preserve

Vector of TRUE/FALSE of length equal to the number of columns:

Preserve the columns corresponding to TRUE values.

out_names

The names of count columns in the output. Must be the same length and order as cols (or unique(groups), if groups is used).

dataset

DEPRECIATED. use "data" instead.

See Also

Other calculations: calc_diff_abund_deseq2(), calc_group_mean(), calc_group_median(), calc_group_rsd(), calc_group_stat(), calc_n_samples(), calc_obs_props(), calc_prop_samples(), calc_taxon_abund(), compare_groups(), counts_to_presence(), zero_low_counts()

Examples

if (FALSE) {
# Parse data for examples
x = parse_tax_data(hmp_otus, class_cols = "lineage", class_sep = ";",
                   class_key = c(tax_rank = "taxon_rank", tax_name = "taxon_name"),
                   class_regex = "^(.+)__(.+)$")
                   
# Rarefy all numeric columns
rarefy_obs(x, "tax_data")

# Rarefy a subset of columns
rarefy_obs(x, "tax_data", cols = c("700035949", "700097855", "700100489"))
rarefy_obs(x, "tax_data", cols = 4:6)
rarefy_obs(x, "tax_data", cols = startsWith(colnames(x$data$tax_data), "70001"))

# Including all other columns in ouput
rarefy_obs(x, "tax_data", other_cols = TRUE)

# Inlcuding specific columns in output
rarefy_obs(x, "tax_data", cols = c("700035949", "700097855", "700100489"),
               other_cols = 2:3)
               
# Rename output columns
rarefy_obs(x, "tax_data", cols = c("700035949", "700097855", "700100489"),
               out_names = c("a", "b", "c"))

}