Issues with regression failing in Bagel 2. Version 0.91 still supported?

[mjafin]

Hi there,
Thanks for providing the code for Bagel, great program.

Long story short, we'd like to fix all random elements in our pipeline for integration tests and the seed setting in later versions of Bagel helps us immensely. I've noticed however that with our test data the linear regression in 2.0 fails so that the cross validation or bootstrapping almost never finish (https://github.com/hart-lab/bagel/blob/master/BAGEL.py#L700)

I've therefore reverted back to 0.91, which doesn't support setting the seed. I've modified it locally to set the random seed and was wondering if you still support the code at https://sourceforge.net/p/bagel-for-knockout-screens/code/ci/master/tree/ and accept patches? Any plans of having the old code as a branch on Github?

Best wishes and thanks again,
Miika

[rooeikim]

Hi Miika,
Thank you for using BAGEL.
The linear regression in v2 can be failed when the sample doesn't meet our thresholds to define a fc window. It usually happened in case of that core-ess and non-ess fc distributions of the sample are indistinguishable or inverted. I recommend to check the fc distributions. I made a simple ipynb code for you. https://github.com/rooeikim/codes
And, I'll port v0.91 to github to keep the legacy code soon and add the option to support setting a seed.

Best regards,
Eiru Kim.

[mjafin]

Thanks Eiru. I modified 0.91 on my side so happy to do a pull request if you want the seed setting incorporated that way.

Regarding v2, rather than exiting when the regression doesn't work how about reverting to some kind of meaningless values or skipping to the next CV/bootstrap iteration? At the moment my analysis randomly never finishes. Or what about using some sort of a regularised regression method? I'm assuming this is some kind of a multicollinearity problem.