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Question about differences between propr versions #23
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Hello again! Thanks for a challenging question. I don't think there were any substantial changes, but I checked the source code and it seems I have updated the default zero-handling procedure. (Diff checker pasted below). Could you try:
and let me know what you get? |
Thanks a lot Thom!!! The values are the same for both propr versions when using expr+1. Now, I still have one question. The problem I have is that I am trying to benchmark on Skinnider's dataset, and I somehow failed to reproduce their values for rho and phs (whereas the other metrics like pearson, spearman, and zi_kendall, had no problem). Do you think that some part of the propr code might depend more on the working environment/ packages/ libraries / etc than the conventional stats::cor(mat, method = 'spearman', ...)? |
Ah, sorry! I never responded! Is it possible things changed from R 3.6 to R 4.0? |
Hey Thom, sorry for the late response! I don't think the problem is between R 3.6 and R 4.0 since I have already tried on both R 3.5 and R 4.0+. I am currently checking with Skinnider to see where is the actual problem. I will keep you updated once we find out the cause |
Hi @suzannejin, did you manage to solve this problem? I know it was some time ago but I'm experiencing a similar issue right now. |
Hey @AlSzmigiel what is the problem for you exactly? Do you find differences between different propr versions, or between different R versions? |
Hi @tpq !
While running propr using an older version (v4.0.0), I found that for some datasets different coefficients were obtained in comparison to the latest propr version. May I ask if some latest changes that affect the computation of the proportionality coefficients were introduced or am I missing something here?
Below you have an example run on a single-cell dataset downloaded from Skinnider et al 2019 (https://github.com/skinnider/SCT-MoA/blob/master/data/geo/filtered/GSE51254.txt.gz)
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