Open antoine4ucsd opened 1 year ago
Thanks for your interest @antoine4ucsd.
The simulations were derived from the impulse model from ImpulseDE. The paper doesn't describe the model in detail but you can see it in the earlier paper or original code: Bioconductor or GitHub. I'm attaching what should be all the relevant files from the private manuscript repository we used to generate figures (from commit 6b8774f1c6b83e7123aaac99f9e20f457f38d6b5
). GitHub won't let me attach .R
files so rename .txt
to .R
:
calc_impulse
function is from their codeI believe LPWC expects there to be complete data without any missing values. However, I'm not seeing any error checking where we enforce that expectation. In our case studies in the paper we removed rows with missing values because they were a proof of concept. If you want to do a real analysis, that may not be an option. Imputation with a temporally-aware approach (like splines or perhaps even fitting the impulse models above if they fit your data well) would be a reasonable choice.
@thevaachandereng we should document the expectations regarding missing values before closing this issue.
thank you so much for sharing these codes and for your detailed response. I will work on it today and keep you updated. Best,
thank you for this interesting approach and for sharing the code. I am really interested in using a similar approach to our dataset. I have a couple of questions: