Purposes—To develop a new heuristic sequence clustering heuristic(EdClust)based on Edlib,with the aim of addressing overestimation of inferred clusters and low seed quality in numerous heuristic clustering algorithm.Methods—In EdClust,the first input sequence becomes the seed for the first cluster.The next input sequence is compared against all existing seeds by using the Edlib C/C++library of sequence alignment.If the similarity is greater than the given threshold,this sequence is added to the corresponding cluster.Otherwise,a new cluster is created,and the sequence becomes the seed.The previous processes are repeated until all the sequences are clustered.Results—EdClust is tested on two widely used databases,demonstrating that EdClust can obtain fewer clusters and a-chieve higher clustering sensitivity.Conclusions—In EdClust,Edlib is used to perform pairwise align-ment,which can find the most similar region at any part of the seed for a query sequence.It's demon-strated that EdClust improves the seed quality and reduces the overestimation of clusters.
维普
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