dada_learn_errors_subset: DADA2 learning the error rates based on a subset of data

In vmikk/metagMisc: Miscellaneous functions for metagenomic analysis

DADA2 learning the error rates based on a subset of data

Description

Function to learn the error rates from a subset of the data (for the big data workflow)

Usage

dada_learn_errors_subset(
  filts,
  n = 25,
  samps = NULL,
  multitr = TRUE,
  verbose = TRUE
)

Arguments

filts	character vector with the names of pre-filtered fastq or fastq.gz files
n	integer, how many samples to choose for learning (will be ignored if samps != NULL)
samps	character vector, which samples to take for learning (overrides n-argument)
multitr	logical, enables multithreading
verbose	logical, shows some additional information

Value

Matrix with estimated error rates that can be used with dada-function.

References

https://benjjneb.github.io/dada2/bigdata.html

See Also

dada

Examples

library(dada2)
# filtF and filtR are character vectors with the full path to fastq.gz-files
errsF <- learn_errors_subset(filtF, n = 30)
errsR <- learn_errors_subset(filtR, samps = attr(errsF, "selected_samples"))

vmikk/metagMisc documentation built on Feb. 14, 2024, 2:29 a.m.