Well I've ended up making the modules for 7 out of 10 of the methods implemented in the pipeline (ABSREL BGM BUSTED FEL FUBAR MEME and SLAC), as they basically all follow the same input schema. I'm working on GARD at the moment but I have a problem with my test dataset

Error:
Internal error 
Internal error in ComputeBranchCache (branch gard.tree.part_1.Node2, eval #348133 ) reversible model cached likelihood =  -7298.887093143881, directly computed likelihood =  -7298.899177285343. This is most likely because a non-reversible model was incorrectly auto-detected (or specified by the model file in environment variables; for smaller errors, this could be due to numerical instability of calculations for larger alignments). To treat numerical errors as warnings, please specify "ENV=TOLERATE_NUMERICAL_ERRORS=1;" as the command line argument. This often resolves the issue, which is indicative of numerical instability.

The test pass if I add "ENV=TOLERATE_NUMERICAL_ERRORS=1;" to the command line in the module. However, I wonder if it should be included in the module itself, as that might prevent this error from showing up in regular analyses? I'm not sure how often it actually occurs. If it's better not to do it, I can just use another test dataset pilfered from Datamonkey (the small one probably). If anyone has any input? @Nina Xiong @Danielle (sorry to bother you but since you're from Pond lab I thought I would use the opportunity 😅)