Reads multiple ninetails read_classes outputs at once.

Batch-loads any number of read_classes prediction files with a single invocation, attaching sample-level metadata from the provided samples_table. Each file is loaded via read_class_single and the results are combined into a single long-format tibble.

Usage

read_class_multiple(samples_table, ...)

Arguments

samples_table

Data frame or tibble containing sample metadata and file paths. Must have at least two columns:

class_path

Character. Path to the read_classes prediction file for each sample.

sample_name

Character/factor. Unique sample identifier.

Additional metadata columns (e.g. group, condition) are preserved and propagated to the output.

...

Additional parameters passed to read_class_single (currently accepts sample_name).

Value

A tibble containing read_classes data for all specified samples, with metadata from samples_table stored as additional columns.

Acknowledgements

Function based on read_polya_multiple from the NanoTail package by P. Krawczyk (smaegol): https://github.com/LRB-IIMCB/nanotail/.

See also

read_class_single for the per-file loader, read_residue_multiple for the analogous residue data loader, merge_nonA_tables for combining class and residue outputs.

Examples

if (FALSE) { # \dontrun{

samples_table <- data.frame(
  class_path = c(path_1, path_2, path_3, path_4),
  sample_name = c("wt_1", "mut_1", "wt_2", "mut_2"),
  group = c("wt", "mut", "wt", "mut"))

classes_data <- ninetails::read_class_multiple(samples_table)

} # }