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I really like your method. I would like to use it on my dataset. I have multi omics data in four different csv files. . From paper, its clear xi are generated as: pool all the feature in one matrix
Now as next step, How to create the "canonical gene expression" and pathway input layer for the MiNet model creation. Could you please elaborate it or provide the code ?
The text was updated successfully, but these errors were encountered:
I really like your method. I would like to use it on my dataset. I have multi omics data in four different csv files. . From paper, its clear xi are generated as: pool all the feature in one matrix
Now as next step, How to create the "canonical gene expression" and pathway input layer for the MiNet model creation. Could you please elaborate it or provide the code ?
Sorry for replying late. The canonical gene expression is controlled by the ordering of the input matrix and the mask between inputs and gene layer. So did the pathway layer.
I really like your method. I would like to use it on my dataset. I have multi omics data in four different csv files. . From paper, its clear xi are generated as: pool all the feature in one matrix
Matrix (3x4)
gene1_exp,gene1_meth,gene1_cnv,gene1_integration
gene2_exp,gene2_meth,gene2_cnv,gene2_integration
gene2_exp,gene2_meth,gene2_cnv,gene2_integration
Now as next step, How to create the "canonical gene expression" and pathway input layer for the MiNet model creation. Could you please elaborate it or provide the code ?
The text was updated successfully, but these errors were encountered: