I am looking at using CD-HIT to efficiently filter my protein sequences dataset by a similarity threshold of 70% (cut-off). More precisely, what I want to achieve is that for all the remaining sequences after filtering, all pairwise sequence similarity scores that can be computed are less than 70%.

Does that mean that I should run CD-HIT on my dataset with similarity threshold=70% (rest of the settings at default values), and then just keep only the "representative" sequences from the resulting cluster files? I have read the guide (http://weizhongli-lab.org/lab-wiki/doku.php?id=cd-hit-user-guide) but I am still not sure of how to use the output.

Linking to the above, how would CD-HIT handle this scenario below or similar ones like this:

  • assuming seq. similarity threshold=70%
  • sim.(seqA, seqB) = 80%
  • sim.(seqA,seqC) = 90%
  • sim.(seqA,seqD) = 65%
  • sim.(seqA, seqE) = 60%
  • sim.(seqD, seqE) = 50%
  • => here, would the method keep just seqE, seqD in the output as sequences satisfying the threshold?


  • $\begingroup$ I don't follow your question. The sequences seqD and seqE do not fall into the seqA|seqB|seqC cluster, nor do the fall into the same cluster, so you will have three clusters, with the type sequences seqA,seqD and seqE. But that's not your question is it? $\endgroup$ Mar 11, 2021 at 12:58


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