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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

} # }