Did they group the ME/CFS and LC cohorts together before doing the significance test to pick 3663 DMFs that were differentially methylated compared to HC? If so, I don't immediately see an issue. Separation from the HCs on the plot would be expected, but not between LC and ME/CFS, I think.
If...
Merged thread
Heart Rate Analysis for ME/CFS
St. Denis, Catherine
Abstract
The article explores Catherine St. Denis's Heart Rate Analysis for ME/CFS, a hybrid work blending medical insight with poetic reflection to illuminate life with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Topics...
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00:00 Amy Proal–An overview of PolyBio’s complex chronic illness research & clinical trials program
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19:46 Mark Painter–T cells as biosensors of viral persistence in Long...
Oh, I don't think this will tell us much. Most of the genes in those gene sets were not important, and the gene sets themselves might not be the best groupings of the genes that were important. Potentially, the overall gene sets/pathways themselves might provide clues, but I wouldn't do anything...
Just want to be sure I understand. You noted down all genes that are included in any of the top gene sets? And identified if they're duplicated in what way?
I have the same concern about the test set being so small.
I wouldn't say their model definitely wouldn't replicate on UK BioBank cohort based on that. The comparison they and I did on the BB is much less sophisticated than if they had actually used their model for classification.
Edit: But...
I thought it might be interesting, but when I go to Genebass and filter by any genes with "NOTCH" in the name, none of the six NOTCH genes are significant at all.
Final thing for now because I am exhausted. I ran GSEA with the cellular component collection since I already ran the same one on the Genebass data.
Link to list of enriched component gene sets in Genebass
I decided not to use collapsePathways here. Since I am comparing if any gene sets match...
Ok, I've run GSEA on the Zhang genes ranked by attention scores with the hallmark and canonical pathways collections:
Hallmark:
Canonical Pathways:
I used collapsePathways to reduce the number of pathways, and it removes about half of them. Interestingly the first two, which seem very...
I'm not sure it's the strongest evidence, but if, as @Utsikt says, there is overlap in diagnosis, and it's not considered a totally unrelated condition, I think that supports the idea that it got number 1 most related because it actually does have genes in common with the ME/CFS group.
I have a basic familiarity. Currently working on getting acquainted with fgsea in R so that I can use the collapsePathways function, which seems useful, and the software I was using doesn't have it. I'd appreciate the help, but no rush!
Ok yes thank you that makes sense.
Yes, that'd be ideal, and actually seems like what they did for their module enrichment of the top 115 genes. I don't understand a lot of the terms like Louvain, but it seems like they made discrete modules from STRING, then used Enrichr on the best matches. I...
Sure, but isn't that what's interesting? The networks of related genes, even if they include genes not actually very useful on their own in this cohort. Which networks did the model "pull higher up" based on its assessment that these networks are useful for classification.
Maybe the divide is...
I get what you're saying, and will have to learn/think about how violating independence may affect the results. Intuitively, it feels like it should work to figure out how any prespecified groups of items are found more near the beginning of any long list of items, which I think is exactly...
@jnmaciuch Do you think GSEA on the Zhang genes might be useful and/or which specific gene set collections would be most useful? They did an enrichment analysis of the top 115 genes and got associations with synapses, proteasomes, and these two:
I assume the 115 gene cutoff is somewhat...
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