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?
Thanks!
seqDandseqEdo not fall into theseqA|seqB|seqCcluster, nor do the fall into the same cluster, so you will have three clusters, with the type sequencesseqA,seqDandseqE. But that's not your question is it? $\endgroup$