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Yes that’s the promise. The issue I’m worried about is whether it actually can deliver. You’re inputting strings of nucleotides and getting out eQTL predictions (with the gene names attributed after the fact), but that was also the format for the training data: input sequences with known eQTL...

Thanks for catching that

[Edit: nevermind, I misread!] For reference this is the location of the strongest SNP in the region in DecodeME, attributed to BNT2A2 here but actually closer to histone genes

This hit is actually right in an intronic region of BNT3A2. Much closer to the BNTs than any of the DecodeME SNPs The plot below is DecodeME results, centered around the SNP from this study (chr6:26,365,679). It would be right above the second "o" where it says "Chromosome 6 (Mb)"

The main thing that makes these results seem more plausible to me is that the narcolepsy results looked similar. [Edit: it seems like there were probably some differences in total area quantified, judging by larger range of cell counts in controls]. Even with the expected variation due to time...

Thanks for the summary. Did they say what the specific genes were? I only had time to quickly skim through the video and couldn’t find the details. I agree with @Jonathan Edwards that the findings are interesting but the team’s interpretation of what it points to should be taken with a hefty...

Nope that’s just good ole fashioned grunt work. Mostly I was trying to figure out if the fact that alphagenome predicted so many genes being strongly affected by one variant was biologically plausible, or if it can be written off as the model hallucinating. If the variants overlap TF binding...

It says “each point represents the surface area measured from a single image” so the only way I can interpret that is: they had a number of images for each participant, chose only one per participant for 1C, and averaged across cells from one image. I’m hoping the legend is wrong because...

Images usually contain more than one cell—I think what they’re saying there is that they had 3 replicate images per sample, making sure that at least 10 cells were visible across all 3. Though the wording is very confusing so maybe something else weird is happening here. [Edit: Either way you...

Just now noticing some weird discrepancies in the number and source of data points being plotted in Figure 1: Legend says: So the right panel for 1B seems to have an issue of pseudoreplication, where each image must have been counted as one point to get that many dots. Just from a quick count...

These are people who failed to get improvement from several drugs that would affect SLPC, but had clinical improvement with dara. I don't think the simple idea of "lupus == SLPC therefore dara treats SLPC-mediated disease" holds here

Sure. For example, having stricter diagnostic criteria to make sure the people you’re studying actually have ME/CFS can end up selecting for people who are temporarily at the worst point of their illness. We know plenty of people can float in between severities. Also inadvertently selecting...

As Jonathan already said you can never safely assume that a clinical trial is randomly sampling out of a natural distribution. Things like selection criteria can and do introduce a lot of bias that even the investigators are unaware of, the intramural study is proof of that too. That’s the whole...

Someone has to cover the dark horses, I guess. Otto Antibody already has many fans.

I don't disagree, interferons are probably secondary to the thing actually giving clinical benefit in this case. What I find interesting is just the possibility that a CD38 mAb could regulate type I interferon production directly by blocking CD38 activity on IFN-I producing cells (and doing so...

Our familiarity with marmalade mostly comes from paddington bear

Potentially. It's interesting here, this supplemental plot tells us that dara does also bind to CD38 on myeloid cells that typically produce type I interferon in lupus: The question is whether the reduced type I interferon response here is a secondary effect of fewer antibodies from plasma...

I looked at one more deletion in another TF-bound regulatory region right next to the most significant SNP a little earlier in the thread. There’s a loss of an AP1 binding site—AP1 has been found to [edit: be relevant in a lot of immune responses including interferon/IL-1B, though it does a lot...

The website is just a quick way of cross referencing a given sequence with known binding motifs for TFs. A binding motif is like a footprint that the transcription factor physically binds to on the DNA (it's the last column in the links). Give the website a nucleotide sequence, it will give you...

Update: very difficult to tell. All the significant hits are in intronic regions of the lncRNA--if they're getting spliced out, they wouldn't be attached to the part of the lncRNA that has complementary specficity to ARFGEF2 (though small regions may have other complementarity...it's not...