Running FLAMES on DecodeME data

ChronicallyOverIt

ChronicallyOverIt

Senior Member (Voting Rights)
Hi all,

Something that has been in the back of my head since the DecodeME data was released was running the newer FLAMES analysis:
github.com

GitHub - Marijn-Schipper/FLAMES: FLAMES: Accurate gene prioritization in GWAS loci

FLAMES: Accurate gene prioritization in GWAS loci. Contribute to Marijn-Schipper/FLAMES development by creating an account on GitHub.
github.com github.com

Somewhat discussed here: https://www.s4me.info/threads/initi...2025-decodeme-collaboration.45490/post-636145

My intention with this thread is that if enough of us get our heads together, I think we me able to run this? I wanted to make a separate thread as I believe if we start working on this it will not be very scientific discussions of the data, and more of a troubleshooting stack overflowish thread. Previously I was able to get the repository up and running with the example, but got stuck at the FINEMAPPING part.

I guess to start off, did anyone else get further? What are the bottle necks? Am I being naive in thinking we can do this? Is there key data we need from the DecodeMe team to accomplish this? Is this something that they are working on?
 
Update for my work tonight, I got a new PC so had to rebuild the environment. Rebuilt and got the example data working.


Interesting I was looking to accomplish step 1 & 2 and found some has already done most of the work!

github.com

GitHub - paolomaccallini-hub/DecodeME: This software performs GWAS analysis on summary statistics generated by DecodeME on 15k ME/CFS patients. In particular, it defines risk loci, performs fine-mapping, and maps selected variants to genes using both

This software performs GWAS analysis on summary statistics generated by DecodeME on 15k ME/CFS patients. In particular, it defines risk loci, performs fine-mapping, and maps selected variants to ge...
github.com github.com

Anyone in contact with this guy? I think he commented his data on a blog by @ME/CFS Science Blog. I also believe these scripts solve the fine mapping issues I ran into before...

Edit, it was this blog: https://mecfsscience.org/genes-pointing-to-the-brain-decodeme-part-ii/
 
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Thanks for trying this. I gave up because my coding skills are rather amateurish. There was also the issue that I wouldn't be entirely sure if it worked or if I had misapplied it somehow.

I was hoping that either researchers would use this in future publications (e.g. the official DecodeME paper) or that the FLAMES authors would integrate this tool into an easier user interface.

But it would be really great if you (with the help of others) could make it work!
 
ME/CFS Science Blog said:
Thanks for trying this. I gave up because my coding skills are rather amateurish. There was also the issue that I wouldn't be entirely sure if it worked or if I had misapplied it somehow.
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My fear as well. I’m hoping by documenting my steps extremely clearly I can at least have others replicate and potentially check my work.

It’s more the biology decisions of the data and lift overs that worry me. Dropping something without having the correct translation. I’ll try to outline my next steps tonight.

How far did you get @ME/CFS Science Blog
 
mariovitali said:
I spoke with Paolo and he said that he should re run the analysis shown on his blog. I will PM him again.

If you want any help on coding I may be of help as I have the time now !
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I read some of Paolos blog, sounds like he is worse in winter :( if it’s too much I would rather not bother him.

I’ll start a google collab tonight. I’m happy to coordinate on here or start a small discord server, up to y’all.
 
Hmm I’m more interested in just running FLAMES on only the decodeME data. I’m not so up to date but i believe this is the highest quality of GWAS data, and want to see what the FLAMES analysis provides more clues.

Still interesting work! Does he have any interest in joining this forum or discussion. If you have the chance please let him know about this thread.
 
Has anyone compared the genes he has highlighted here to the genes in the decodeMe Magma?
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From what I saw, the following genes from Paolo's list are new :

OTX1
WDPCP
UGP2
VPS54
PREX1

There are several reasons why these may be important. More specifically (not meant to be a complete list of related functions):

OTX1 : Neuronal involvement and could be important for susceptibility to neuronal excitability (study in mice) :

https://onlinelibrary.wiley.com/doi/abs/10.1046/j.0953-816x.2001.01723.x

WDPCP : Related to cilia signalling. With a bit of searching, a hypothesis here is that we may be looking at functional ciliopathy not congenital.

UGP2 : Very important for N-Linked glycosylation (a target identified in 2015 via machine learning).

VPS54 : Points to vesicular trafficking

PREX1 : GPCR-related signalling. Could be a signal amplifier.
 
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