Identify parent lineages with LAPIS cov-spectrum about ncov-recombinant HOT 8 CLOSED

• 1. Extract the mutations by region predicted in sc2rf.
  • Add an additional column mutations in sc2rf.
  • Add an additional column sc2rf_regions_mutations in sc2rf/postprocess.py.
• 2. Query cov-spectrum to get a JSON of lineage proportion for each region.

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What about private mutations though? We might want to exclude those from the cov-spectrum query.

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I prefer the unlabeled private mutations reported by nextclade, because that is not based on a custom selection of lineages.

from ncov-recombinant.

The designated recombinants are tricky, because their "private mutations" are not private. To get better parent lineages, I'd probably have to use the nextclade dataset without recombinants.

How about I try and putting the alignment that will go into faToVcf through that version of nextclade?

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Group proportions for sub-lineages!

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The optional param lapis is removed from sc2rf_recombinants , as this is now an essential feature.

from ncov-recombinant.

I think the major obstacle to grouping proportion for sub-lineages, are the aliases. This would likely require a separate rule, to download the lineages hierarchy and aliases and process this into a tree structure (newick). This tree structure could be processed to get descendant lineages.

This would involve adding biopython to the conda environment.

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I'm going to open up a new issue for the sub-lineage proportion grouping.

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