Open RTMorris1 opened 1 week ago
Hi @RTMorris1 thanks for your interest in the tool. A couple questions that might help get to the bottom of this:
I can also take a look at the files that were uploaded to Zenodo as well as the joint_quantifications.csv
that is part of the package release. We're still in pre-beta phase so it's possible that there is a bug hiding somewhere.
Lincoln
Hi Lincoln, 1.) the OS is Ubuntu 20.04 2.) The command used was lupine impute --outpath lupine_test1c_out/ --device cuda joint_quantifications.csv
3.) i want to use the tool to impute missing quantified protein values for >1000 in house TMT MS3 tissue experiments. I don't want to combine them with the CPTAC experimental data.
I was running lupine on the joint quantification file in order to test the tool.
This should be resolved by commit ea6735ab62f8362e16629b9f056b558ebefad35e. This was hard to track down but I think the learning rate for the Adam optimizer was set too high by default.
For your use case, considering you have >1000 TMT experiments, you should be able to skip directly to the impute
step directly on a matrix of protein (or peptide) quants (skipping the convert
and join
steps).
Let me know if this patch works for you and I'll close this issue.
I am having an issue running Lupine. I installed the software and downloaded the joint quantification data from github without any difficulty. However when I ran the tool on the joint quantification data table I was surprised to see that over 97% of the missing values were imputed with negative values. When I compared my results to the published results available on zenodo.org I didn't see any negative values (focusing on the BRCA results). I ran lupine with the following command: lupine impute --outpath lupine_test1c_out/ --device cuda joint_quantifications.csv