Correlation matrix from circosplot

Hi all!
Based on a previous post, I’m really happy with the integration results I’ve been able to achieve with this package!
I was hoping for a clarification on some results
So I am trying to understand the correlation matrix extracted from my circos plot. Given I have 4 blocks, based on my code I would expect this matrix to have all the features from the first component in rows and columns, and there would be the typical “triangle” structure where autocorrelations are perfect (1) while x vs y and y vs x correlation coefficients are the same. However, this is not the case. While the latter expectation holds true, the values for autocorrelations are <1 and seem more or less random. I’ve attached a screenshot below.

Is there a reason for this? How can I interpret these values? Does this have to do with the design matrix used for building the model? I have experimented with both full and data-driven design matrices, and neither give the expected result.

Thanks so much!

hi @mirG,

The x vs y and y vs x similarities are the same.

The calculation of the correlation is described in Visualising associations between paired ‘omics’ data sets | BioData Mining | Full Text and summarised in the slides below. We dont calculate direct cross-correlations, but correlations with respect to the component. These calculations are designed only for cross-correlations (i.e x with y, but not x with x) so you should ignore x vs x (or set it to 1 if you need this output for downstream analysis).

Screen Shot 2023-10-13 at 08.40.17


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