Comments (2)
jisoopark
commented on August 24, 2024
At this moment, we haven't published the RLIPP script as the current version is tailored to our analysis. Many parts are hard-coded and there are many moving parts that can be customized depending on the objective of users' analyses. We will work on a generalized version of the script and share it as soon as it is ready.
The RLIPP score calculation can be seen as simple as it trains linear regression models for each subsystem and the concatenation of its children. The features of the linear models can be either raw neuron values or principle components depending on where you observe a stronger signal for your analysis. While we are working on the generalized version of the RLIPP script, please feel free to modify and implement the idea. Thanks, and sorry for the inconvenience.
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1512474508
commented on August 24, 2024
Good jobs！Thanks
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Related Issues (20)
- Try to run it on google colab/ jupyter notebook, report error in "final_input = torch.cat((term_NN_out_map[self.root], drug_out), 1)" (line 177 of drugcell_NN.py)) HOT 1
- Output Format Not Explained HOT 2
- Resource Guide Missing HOT 3
- Installation Instructions Require Anaconda HOT 1
- Mistakes in User Guide HOT 1
- Interpretable Pathway Models not Documented
- how to hash the morgen fingerprint into binary drug feature HOT 1
- Mistake on commandline_train.sh HOT 1
- RLIPP Calulcation
- Question about the network uncertainty
- Release of full training data HOT 1
- Reproducibility of the ontology hierarchy (VNN) HOT 1
- Question about Evaluation Metric
- new cell feature
- pretrained_model avaliable? HOT 2
- about Figure 3
- will provide train data preprocessing code
- 18 GO terms do not have genes defined HOT 6
- failed to download pretrained model at https://drugcell.ucsd.edu/downloads/ HOT 2
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