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I'm looking for some software that can "efficiently" (time and memory) compute the exact percentage of non-unique k-mers in a genome for given k. I don't need the k-mers or the abundances itself, I just need the percentage.

Alternatively, the result could be:

  1. the number of different k-mers observed in the genome
  2. the number of unique k-mers, i.e. k-mers that occur only once in the genome, or the number of non-unique k-mers, i.e., k-mers that occur more than once in the genome.

which can be easily used to compute the requested percentage.

Requested features:

  • don't count k-mers with ambiguous nucleotides
  • count a k-mer and its reverse complement together
  • k upto 50 or 100
  • for large genomes (upto some GB)
  • efficiency

For the study in mind, I like to vary k. Hence, I will run the software several times with different k.

Any help is welcome.

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    $\begingroup$ Welcome to the site. What is your current solution? Which non-efficient programs have you found (To avoid proposing them)? Can't the other answers in the k-mer help you to make that program? $\endgroup$ – llrs Mar 14 '18 at 10:14
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You can do all of that with khmer. For example, abundance-dist-single.py produces a file with columns: k-mer abundance, k-mer count, cumulative count, and fraction of total distinct k-mers. So for question 1 you would sum column 2. For question 2 you would just get thek-mer countassociated with ak-mer abundance` of 1.

That package also provides a python API (see the read the docs link above) if you need to customize things more.

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  • $\begingroup$ Thanks a lot for that hint. I made a first test of khmer using A.thaliana: python abundance-dist-single.py -k <k> -b <genome> <out>. It looks great. It's fast and easy to use. However, I get an error for k > 32. Is there a way to go further than 32? $\endgroup$ – Jens Mar 20 '18 at 21:49
  • $\begingroup$ I'm not sure it's possible with the command line script, but it appears to be possible in the API. $\endgroup$ – Devon Ryan Mar 21 '18 at 7:43
  • $\begingroup$ Thanks for that hint, I'll check that. However, I also found out for some examples (and reading the documentation/papers afterwards ;) that it is not exact. Hence, I currently also use the parameters -N 20 -x 1E7 to avoid too many mistakes. Just in case anyone like to do a similar case study. In addition, I have some problems with some species where khmer states ERROR: abundance distribution is uniformly zero; nothing to report. Please verify that the input files are valid. The files seem to be okay and have been used in other analysis. Any ideas? $\endgroup$ – Jens Mar 21 '18 at 8:45
  • $\begingroup$ No, sorry, I've never seen that error. $\endgroup$ – Devon Ryan Mar 21 '18 at 12:28

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