Re: [Biopython] Calculating NS and S over a given sequence

Zheng Ruan <[email protected]> Thu, 30 Sep 2021 09:32:38 -0400
Newsgroups gmane.comp.python.bio.general
Message-ID <CABM7aFrHdkrnEH1SccNfyOxZZb11Tq7cRExCUkycHb4NzBRN3A@mail.gmail.com>
Hi Pablo,

You can simply use cal_dn_ds(ref_seq, sample_seq) to achieve this. If you
have multiple sample_seqs, you may iterate all of them.

Internally, cal_dn_ds determines the N and S sites by averaging the N and S
sites counted from both the ref_seq and sample seq. If you specify the NG86
method, it does the log transform as you show in the figure.

Best,
Zheng

On Thu, Sep 30, 2021 at 5:24 AM Riesgo Ferreiro, Pablo <
[email protected]> wrote:

> Hi all,
>
>
>
>
>
> I am new to this mailing list. First of all many thanks for your work, I
> have happily used Biopython in several projects before.
>
>
>
> I have a need to compute the dN/dS ratio over a set of samples of the same
> species. I know this is not great 10.1371/journal.pgen.1000304, but still.
> I have found this feature in biopython calculating the dN/dS between
> sequences:
> https://biopython.org/docs/1.76/api/Bio.codonalign.codonseq.html#Bio.codonalign.codonseq.cal_dn_ds,
> but this does not cover my needs.
>
>
>
> What I need is to compute dN/dS based on the count of mutations over a set
> of samples as explained at
> https://bioinformatics.cvr.ac.uk/calculating-dnds-for-ngs-datasets/
>
>
>
> [image: cid:7c03806e-bbb0-47b1-9c49-3c53e33af83e]
>
>
>
> N and S is dependent on the reference sequence and independent on the
> samples. N and S can be calculated on different genomic regions (eg: coding
> region, transcript, exon, domain, etc.). The simplest input for this tool
> would be a given ORF sequence and you would think of more complete things
> as a GFF file.
>
>
>
> It is a small thing, but unless anyone knows of an existing
> implementation, I think it may be useful to others. Do you think this would
> be a valuable contribution to biopython?
>
>
>
>
>
>
>
> Best wishes,
>
>
>
> Pablo Riesgo Ferreiro
>
> Computational Medicine
>
>
>
> *TRON*
>
> Translationale Onkologie an der Universitätsmedizin der
>
> Johannes Gutenberg-Universität Mainz gemeinnützige GmbH
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