Skip to contents

Calculate edit distance with sliding window (HW mode)

Source: R/ninetails_misc_helper_functions.R
edit_distance_hw.Rd

Computes the minimum edit distance between a query sequence and a target sequence using a sliding window approach (HW: Hamming-like Window mode). The query is aligned to all possible substrings of the target of equal length, and the minimum distance across all alignments is returned.

Usage

edit_distance_hw(query, target)

Arguments

query

Character string. The primer or query sequence to search for.

target

Character string. The target sequence window to search within.

Value

Integer. The minimum Damerau–Levenshtein edit distance found across all possible sliding window alignments.

Details

Edit distance is computed using the Damerau–Levenshtein distance, as implemented by adist, which accounts for insertions, deletions, substitutions, and transpositions.

The sliding-window strategy for edit distance calculation is adapted from approaches commonly used in natural language processing; see the reference below for an illustrative example.

References

Silge, J. (2019). *Natural Language Processing in R: Edit Distance*. R-bloggers. https://www.r-bloggers.com/2019/04/natural-language-processing-in-r-edit-distance/

See also

detect_orientation_single where this function is used for fuzzy primer matching in read orientation classification.

Examples

if (FALSE) { # \dontrun{

edit_distance_hw("ATCG", "XXATCGXX")
# Returns 0 (perfect match inside target)

edit_distance_hw("ATCG", "ATTT")
# Returns minimum distance across sliding windows

} # }