Conversion to count table function with prevalence filter

Conversion to count table function with prevalence filter

Usage

get_count_table(
  abund.path = NULL,
  abund.table = NULL,
  sample.id = NULL,
  prev.min,
  verbatim = TRUE,
  msp = NULL
)

Source

This function is adapted from the same name function in OneNet package (version 0.3.1), which is licensed under the MIT License. Original copyright (c) 2021-2024 INRAE.

    The MIT License text for the original package is as follows:
    ---
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE.
    ---

Arguments

abund.path

String. Path to the abundance table

abund.table

Dataframe. Abundance table, it should have the bacterial species names as first column

sample.id

String vector. IDs of samples to keep in the final table

prev.min

Numeric. The value is between 0 and 1 and corresponds to the minimal prevalence threshold of bacterial species to keep in the final table

verbatim

Boolean. Controls verbosity

msp

String vector. It indicates bacterial species names, if they are not specified in the abundance table first column

Value

A list containing

data:

the final count table (tibble)

prevalences:

a tibble gathering the prevalence of each bacterial species

Examples

tiny_data <- data.frame(
  msp_name = c("msp_1", "msp_2", "msp_3", "msp_4"),
  SAMPLE1 = c(0, 1.328425e-06, 0, 1.527688e-07),
  SAMPLE2 = c(1.251707e-07, 1.251707e-07, 3.985320e-07, 0),
  SAMPLE3 = c(0, 0, 4.926046e-09, 5.626392e-06),
  SAMPLE4 = c(0, 0, 2.98320e-05, 0)
)
# Applying a prevalence filter of 30% on the new count_table
count_table <- get_count_table(
  abund.table = tiny_data,
  sample.id = colnames(tiny_data),
  prev.min = 0.3
)
#> Preprocessing step output for species prevalence>30% : 
#>    -from 4 to 3 species
#>    -from 50% to 41.7% zero values.