Pyvorin for Genomics

Sequence Alignment

Smith-Waterman and Needleman-Wunsch algorithms are textbook compilation targets.

def smith_waterman(seq1, seq2, match=2, mismatch=-1, gap=-1):
    score = [[0] * (len(seq2) + 1) for _ in range(len(seq1) + 1)]
    max_score = 0
    for i in range(1, len(seq1) + 1):
        for j in range(1, len(seq2) + 1):
            match_score = score[i-1][j-1] + (match if seq1[i-1] == seq2[j-1] else mismatch)
            delete = score[i-1][j] + gap
            insert = score[i][j-1] + gap
            score[i][j] = max(0, match_score, delete, insert)
            max_score = max(max_score, score[i][j])
    return max_score

K-mer Counting

Count overlapping subsequences for assembly and classification.

Variant Calling Pipelines

Quality score recalibration and allele frequency filtering.