singing-scientist
commented
3 years ago Thanks a lot for your interest in SNPGenie, @andreaswallberg! Regarding the questions:
- Yes, each VCF file is treated as its own pooled sample from a population. The only exception to this is when using SNPGenie's
--vcfformat=4, where each additional SAMPLE column is treated as its own (pooled) sample. This is the only format which supports multiple samples in the same VCF file.
I think this speaks to your question, as it sounds like your "sample" columns each represent one individual. Because SNPGenie expects each will represent a pool, this approach will not work. It will instead be necessary to bioinformatically "pool" the individuals you've sequenced, e.g., summarize them in a single VCF file for use with whichever SNPGenie VCF format is most convenient.
Ah! Looks like I got ahead of myself. Indeed, if Freebayes the bioinformatically pooled "summary" data in this way, using --vcfformat=2 should ignore the "sample" columns altogether and just use the DP and AF flags — so you should be good to go!
- To me, this is a surprisingly complicated issue. First of all, SNPGenie computes raw "mean p" distances, as is appropriate for π (i.e. low levels of diversity). Depending on how distant the other species are, this may or may not be appropriate, i.e., a multiple hits correction (Jukes-Cantor, Kimura 2-parameter, or more complex) may be required. If the two species have a raw p distance of more than about 0.1 (10% divergence), then I recommend just using Jukes-Cantor. But if it gets much more, the between-species approach might instead benefit from other approaches, like Bayesian tree/site-based models in HyPhy. If you're already generating "pseudo-alignments" of your samples using #34 anyway, this should not be too difficult.
I now see your question about PAML, etc. — that is fine, too. What you suggest would be ideal, and if I'd been a better coder when writing SNPGenie I surely would have used a modular approach that would allow another dN/dS engine to be "plugged in", as it were. Unfortunately, SNPGenie is anything but modular and such a change would require a major rewrite that I (sadly) currently don't have time for. I do hope to take a crack at this whole thing again in coming years, using Python this time, and will make modularization a priority!
About the question of orthology, I think that your approach of mapping reads from different species to the same reference is a clever one. Depending on how distant the species are, you might run into problems with indels and rearrangements, etc. In my ideal world, it would be best to first align the references of all species together using a pipeline like Enredo/Pecan/Ortheus to determine which sites are homologous; exclude any sites with multiple hits in the alignment (i.e. exclude any sites that are even possibly duplications/paralogs); map reads separately to each reference; and finally convert the coordinates from each reference to one one the species' references using the multi-species alignment. This is of course too perfectionistic and terribly tedious; it's probably fine to use your approach so long as you're somehow trying to correct for possible biases, e.g., read mapping bias that could occur due to regions of divergence or rearrangements.
- Each FASTA reference — whether it's a chromosome or a small contig — must have its own VCF and own GTF file for use with SNPGenie, and the coordinates of the 3 should correspond. That is, one SNPGenie run involves a single trio of FASTA/GTF/VCF. It isn't smart and can't figure out what you mean, but simply believes that site 1 of the FASTA is site 1 in the GTF and VCF files; however, it should throw an error if anything is out of bounds.
Could you explain what you mean by accessions in whether the revcom script will "handle multiple accessions as is"?
Hope at least some of this is helpful!
andreaswallberg
Dear @cwnelson88 ,
Thanks for implementing these solutions in these scripts! These are hugely time-saving for anyone interested in accomplishing gene-centered population genomics!
I have some questions which I think were partly explained in #34 and #35 but I will take the liberty to ask again, just to be sure.
Lets say I work with discrete libraries from individuals sampled from one population (one library, one read-group sample and one column per individual following the "FORMAT" column on every line with a variant) and produce a VCF with a tool like Freebayes (VCFv4.2). The intention is to compute πN/πS across all these individuals, i.e. to treat them as a single population.
If run with --vcfformat=4, will these samples be treated as a single or separate populations?
Freebayes also outputs the global DP and AF tags in the INFO column. Will SNPGenie use these instead of the "SAMPLE" columns? Can I specify --vcfformat=2 to enforce using these tags and effectively parse the multi-sample VCF as a single-population VCF?
I suspect one answer to this is to map data from other species to the same reference, and generate one VCF per species. Depending on genetic distance, this will contain quite a few gene regions with variants fixed for a non-reference alternate allele. Using the script from #34, species-specific sequences can then be exported and easily concatenated. This mapping approach side-steps the issue of orthology-detection using external tools.
Does this sound reasonable to you?
For dN/dS, is there any correction for multiple substitutions when estimating dN and dS?
Corrected dN and dS could possibly be computed separately using PAML. Would it be possible for you to implement a way of optionally side-loading those stats from a simple table, such that they can replace or complement the internal computation of dN/dS and be incorporated in the standard summary statistics computed by the program?
Must all included contigs have a gene model? Will the reverse-complement script handle multiple accessions as is, or will I need to use alternative solutions?
Cheers!