Reshapes nonadenosine_residues data frame to wide format.

Pivots the prediction column of the nonadenosine_residues data frame into three separate columns (prediction_C, prediction_G, prediction_U), each containing the count of respective non-A residues per read. An additional nonA_residues column provides a CIGAR-like summary string listing all non-A positions from 5' to 3', separated by ":".

Usage

spread_nonA_residues(residue_data)

Arguments

residue_data

Data frame or tibble containing non-A residue predictions produced by the ninetails pipeline (filename typically ends with _nonadenosine_residues.tsv). Required columns: readname, group, prediction, est_nonA_pos. The qc_tag column may be character (Guppy/nanopolish) or numeric (Dorado MAPQ).

Value

A tibble in wide format with one row per read. In addition to the original columns (minus est_nonA_pos and prediction), the following are added:

prediction_C

Integer. Number of C residues detected in the read.

prediction_G

Integer. Number of G residues detected in the read.

prediction_U

Integer. Number of U residues detected in the read.

nonA_residues

Character. CIGAR-like string summarising all non-A positions (e.g. "C12:G25:U40").

Details

This function supports data from both the legacy Guppy/nanopolish pipeline and the Dorado pipeline. The qc_tag column may be either character (Guppy: "PASS", "SUFFCLIP", etc.) or numeric (Dorado: MAPQ score). Both types are handled transparently and preserved in the output.

See also

merge_nonA_tables which calls this function internally, read_residue_single for loading residue data.

Examples

if (FALSE) { # \dontrun{

spread_table <- ninetails::spread_nonA_residues(
  residue_data = residue_data)

} # }