I have a 5000 X 32 X 10 3D array of gene expression data that I would like to apply clustering and dimensionality reduction on.
The dimensions represent the following:
I have 5000 genes, measured in 32 different mutant strains, each in one of 10 environmental conditions. (mean = 0, var = 1)
I'm trying to do something akin to biclustering or SVD, but have no experience with 3D arrays.
I found a CV post talking about SVD on 3D arrays , but was hoping to get some more information about how to get started, and what I should try first.
Fellow researchers have suggested that I simply flatten the array into a 5000 X 320 2D array, but I am hesitant because I feel like I am loosing information about the relationships between columns.