Some questions about the LGG LUAD KIRC experiment

[Y-Claw]

Are the mrna and CNVS used in your LGG,LUAD,KIRC experiments logarithmic or normalized? May I ask whether the network structure and network hyperparameters are consistent with the gbm experiment?

[mskspi]

We used normalized mRNA data and actual copy numbers for CNV, all downloaded from cBioPortal.
The network architecture is the same for all cancers, but was trained, separately, for each cancer.

[Y-Claw]

Could you please tell me whether the specific normalization method used is linear normalization, z-score or other normalization algorithms, as this may cause slight fluctuations in the results.

[mskspi]

We used z-transformed gene expression data.

[Y-Claw]

Thank you very much. Just to be sure, you used the raw data for methylation in the experiment? Z-transformed mRNA is mrna expression z-scores relative to diploid samples or transformed by the original mrna expression？

[mskspi]

Sorry. I checked the data we used again. In this study, we used data_mrna_affymetrix_microarray. I was confused with our other studies where we analyzed z-transformed gene expression data. For methylation, we used the raw data.

[Y-Claw]

For GBM, there is plenty of microarray data, but for directly downloaded from the http://www.cbioportal.org/, LGG LUAD KIRC microarray data that is not enough. May I ask whether you downloaded the data directly from www.cbioportal.org or obtained it by other means?

[mskspi]

For GBM, you used microarray gene expression data due to much more samples compared to RNA-Seq data. I think that GBM is the only cancer in TCGA with the smaller number of samples in RNA-Seq than microarray. For other cancers, we used RNA-Seq gene expression data. Yes, we downloaded all data from cBioPortal. After our work, cBioPortal provides more data, for example, several types of RNA-Seq expression data with different normalization methods. I will check the file names for other cancers to find out the data we used.

[mskspi]

For other cancers, we used "data_mrna_seq_v2_rsem_zscores_ref_diploid_samples.txt" for gene expression data.

[Y-Claw]

Thank you. I'll try again.

[Y-Claw]

Even if we aligned the raw data, I still couldn't achieve the results reported in the paper on the other data. There are still some data processing details that could make a difference, but it's not a good idea to keep bothering. Can you provide the code for your experiments on other data sets? I'll check the questions myself.

[mskspi]

Did you make pathway images that need to be used in our model?

[Y-Claw]

Do you mean that the other three datasets use different pathways than GBM? The pathway that has to be re-selected for each cancer？

[mskspi]

The input data to our model are pathway images generated using PCA on three multi-omics data.
I meant that "did you make the input pathway images?".

[Y-Claw]

Yes, I use pathway images generated using PCA on three multi-omics data as input.

[mskspi]

Files for lgg were added. Please note that the threshold for other cancers to define long-term survival is 36 months.