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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">Cheers Alexey thanks for the update.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">PS sorry for the delay getting back to you about your question on caching – my use-case is making a
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">multivariate k-mer distribution, across many samples. For each sample (= usually a fastq file) ,
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">the program checks if there is already a cached univariate distribution for that sample, and if so it will use that.
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">If not it will build and cache the univariate distribution. This is useful in the case of a restart
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">of the multivariate build, and also in case I want to make a different multivariate build
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">– e.g. add some more samples. Each univariate distribution is reasonably costly to build ,
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">as I am usually processing (and sub-sampling) a large fastq file – so I don’t want to have to
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US">rebuild those.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#1F497D;mso-fareast-language:EN-US"><o:p> </o:p></span></p>
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<p class="MsoNormal"><b><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri",sans-serif">From:</span></b><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri",sans-serif"> Biopython [mailto:biopython-bounces+alan.mcculloch=agresearch.co.nz@mailman.open-bio.org]
<b>On Behalf Of </b>Alexey Morozov<br>
<b>Sent:</b> Wednesday, 15 February 2017 7:44 p.m.<br>
<b>Cc:</b> biopython@biopython.org<br>
<b>Subject:</b> Re: [Biopython] Support for k-mer analyses?<o:p></o:p></span></p>
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<p class="MsoNormal">As there is not so much interest in this task (and people in biopython-dev were uncertain over whether it'd be useful to include kmer module into Biopython distriution), I've decided not to make it. If anyone needs a (non-Biopython) kmer
library, there already are several. I haven't done a proper comparison, but kPAL seems most developed.<o:p></o:p></p>
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<p class="MsoNormal">2017-02-08 20:41 GMT+08:00 Alexey Morozov <<a href="mailto:alexeymorozov1991@gmail.com" target="_blank">alexeymorozov1991@gmail.com</a>>:<o:p></o:p></p>
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<p class="MsoNormal">Hi Alan, thanks for your feedback.<br>
You've thrown some ideas that haven't crossed my mind. I was just wondering: why did you even find it necessary to cache distributions? What was the scale of your work? In my experience, aminoacid distributions of six complete eukaryotic proteomes up to k of
6 or 7 could fit into something like seven or so gigs (with no optimisation, without even numpy), so I thought nucleotide distributions will be prohibitive in terms of RAM only when there are tens of them.<o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Alexey Morozov,<br>
LIN SB RAS, bioinformatics group.<br>
Irkutsk, Russia.</span><o:p></o:p></p>
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