I was trying a couple of tools: Morph Server and RigidFinder and in both cases I get a server error indicating that files could not be written. Specifically, RigidFinder complains: "Cann’t write to file ‘/tmp/rid74285/upfile1.pdb’." and Morph Server says "Can’t create morph directory!". If this site is still being maintained, please consider addressing these issues.
Thank you for your interest in our servers and for letting us know of
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Rigidfinder’s disk filled up. I cleared some space and it should be
Molmovdb, however, is a more complicated issue. It needs an upgrade
since it is more than 15 years old. Occasionally, we simply roll back
to a previous version but then any submissions would be lost. We also
cannot guarantee when the next roll back would be.
We apologize for any inconvenience this may have caused. We provide
related software in our FAQs for those who are interested.
I am contacting you as the corresponding author for the paper: "GRAM: A generalized model to predict the molecular effect of a non-coding variant in a cell-type specific manner." PLoS genetics 15.8 (2019): e1007860.
I would like to express my thanks to you and your group for developing & publishing GRAM. I have recently tested it out and the results have been most interesting.
I have begun to work with eQTL analysis only recently and as a result, I was wondering what you would recommend as a multiple testing correction method for GRAM score based eQTL analysis?
From the literature I have seen that standard multiple testing correction methods such as Bonferroni & Benjamini-Hochberg have be considered too conservative for regular eQTL analysis as they do not take linkage disequilibrium into account, and several permutation testing based approaches have been published specifically for eQTL as a result (e.g. eigenMT). However, as you have demonstrated GRAM score based eQTL to be able to differentiate the regulatory effects of variants in linkage disequilibrium, I am unsure whether such methods would be appropriate here.
One of the application scenarios of using GRAM is fine-mapping, which suppose that you have a list of eQTL and its LD associated mutations. If you don’t have eQTL and want to try it on eQTL identification, maybe one way is you compare the gram score with a normally distributed background (use tens of thousands of background/random selected mutations) and infer a p-value of the GRAM score of a variant relative to the background, then use BH or FDR method to do the multi-testing correction.
Frankly speaking, this is a very great point to extend our GRAM. We may also consider testing this recently. The most computation-intensive part of this to calculate deepbind score for background variants, which will take a long time if we want to test millions of background variants. If you have any feedback, further questions or preliminary findings regarding this, please feel free to let us know.
I’m having trouble with the multi-chain morph server. My protein includes chains that are designated as an upper case “A” and lower case “a”. When I upload the PDB file and specify all chains including A and a, the resulting Morph PDB file does not contain the lower case chain a. Is there any way to fix this problem?
Thank you for reaching out to us regarding the morph server. It is perhaps the case that the server is internally case-insensitive with regard to the chain. If possible, I would suggest changing chain "a" to a different letter in the PDB input file (ie, by changing "a" to "B" using a simple script). Then, once you get your output from the server, you can again change chain "B" to the original label chain "a".