Fig. 5

Conceptual overview of EMERALD’s safety window calculation workflow. As input EMERALD receives a set of clusters in fasta format. For example, such protein sequence clusters can be generated using DIAMOND DeepClust or alternative clustering methods. Next, users can specify the scoring matrix (e.g., BLOSUM62) according to which optimal alignment configurations will be determined. Each cluster member sequence is then globally aligned against the cluster representative sequence (centroid) using the pairwise Needleman-Wunsch alignment algorithm. The resulting dynamic programming (DP) matrix of each pairwise comparison is then encoded as a graph data structure to search for optimal and suboptimal alignment paths according to the selected scoring matrix and the threshold configurations defining the suboptimal alignment space. Once all alignment-safe intervals are computed, EMERALD projects these safety intervals (safety windows) back to the representative sequence, thereby annotating the sequence intervals that are robust across all possible alignment configurations within the suboptimal alignment space