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@jbloom would be good to also include Ne5Gc functional selection data in the phenotype list. I think we want to show the increase in Neu5Gc usage and we have this data in the main flu repo here (it's not in the phenotypes summary file as we're not using it in the any publication yet).
The text was updated successfully, but these errors were encountered:
@Bernadetadad, I'm happy to do this, but can you process the data you want plotted better first?
For instance, for SA26 we just took values with positive differences (better on SA26) and overall improved entry on SA26 cells. The repo for the H5 DMS makes a file with these increase SA26 usage values.
In contrast, the file you linked to just has the raw differences taken over all values, not just then ones causing both relative and absolute improvements.
Also, what filters should be applied to times_seen and diffference_std?
In general, this should be sorted out in the H5 DMS analysis repo. So for instance, if you only want the increases, make a rule like process_SA26_improvement in custom_rules.smk to generate that file. Alternatively, if you just want the raw differences let me know.
@Bernadetadad, no rush if it's not a current priority, but just re-upping above issue that I need more clarity on what data you want plotted as mentioned above.
@jbloom would be good to also include Ne5Gc functional selection data in the phenotype list. I think we want to show the increase in Neu5Gc usage and we have this data in the main flu repo here (it's not in the phenotypes summary file as we're not using it in the any publication yet).
The text was updated successfully, but these errors were encountered: