A single line often inverts meaning once you see what it
answers, so neighbouring messages are always shown.
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As for the Fucking weather analogy it's false. In fact the weather analogy fits much more to your Nature response toGVP. What really happens is that you detect "outbreaks" of weather systems first [you can see some of these on the attached map] then you can track and predict where they go and when they go. I just wasted 2 days prepping forSally that for days was said to be heading straight to NOLa and ended up 200 miles to the east - Katrina was goingto Pennsicola, FL as a Tropical Storm - wrong- the predictions are not perfect. [shared file(s): image.png]
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Just had the following email. It seems reasonable to get to the bottom of what is up with RaTG13 (I imagine it was sloppy work under extreme pressure). Obviously RaTG13 isn't the whole story and the nutters' obsession with it ismisplaced (the existence of the pangolins and RmYN02 tell you almost as much). ```Dear Andrew,I was recently contacted by a national fact-checking body, run by Norwegian media outlets. The topic was the conspiracy surrounding an alleged release of sars-cov-2 from a Chinese lab. They pointed me to this so-called Yan-report, detailing how sars-cov-2 could possibly have been generated by functional genetics. The "Yan-report" seems obsessed with RaTG13, and cite a number of preprints (most crap, but some less so)questioning the veracity of the sequence. As RaTG13 is kind of central in arguments re the origin of sars-cov-2, Iwanted to have a quick look at the sequence data.I am looking at this now together with my colleague Ola Brynildsrud, and so far, we have not been able to re-create the RaTG13 genome in GenBank from the published metagenome fastqs and sanger amplicons published with the RaTG13 genome: paper:https://www.nature.com/articles/s41586-020-2012-7sequence data:https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRP249482&o=acc_s%3AaI wanted to check whether any of you proper Covid people have looked into this dataset, or simply used the published GenBank sequence. The best would probably be to post the question on virological, but I dont have a userthere.It might well be that the authors have been sloppy in uploading all their raw sequence data, but as said, the published raw data does not seem to be enough to generate the RaTG13 assembly, not even when we have said assembly to align reads against. But we're still working on this. Kind regards,Vegard EldholmNorwegian Institute of Public Health```I don't know how much further you want to get into this @Kristian Andersen but I think he is going to email you.
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(I just don't know enough about sequencing bioinformatics and genome assembly to look at this).
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I might take a look at the sequence data - overall, I have no concerns though given that this is how sequencing oflow-coverage genomes often occurs. Patchwork....
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2020-09-17 07:01
Andrew Rambaut
I guess the question is has there been any 'imputation'? From the above it would seem they can't even get the consensus when they map to the actual consensus?
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It would also matter which bits are low coverage. I would prefer to move on but it would be good to be armed with the knowledge - who knows where this will go next.
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I suspect the data is scattered across repos
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I agree with Andrew that the main point is that our analysis would not have changed much at all without RaTG13. The pangolin CoVs (that Alina seems focused on) and other BtCoVs were sufficient for the Proximal Origins analysis. I do recall a PR that talked of a 99% CoV that unfortunately never came.
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> Update from Vegard: ```Quick update: We were in the end able to obtain a decent assembly of RaTG13. The description of their approachis lacking to say the least, but the genome seems legit enough, and seems extremely unlikely to involve any sort offraud.We'll post a little commenn on virological, as there might be others looking into the same question.```