mutual rank values for distance matrix formation for co-expression analysis
We know that earlier version of co-expression database showed that Pearson correlation coefficient (PCC) is used to calculate the mutual rank (MR) values for creating a co-expression network. However, the latest version has neglected the PCC values and displays only the MR data. So how can we use MR to form a Euclidean distance matrix in co-expression analysis
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seemaviriyala •
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I suppose, If you do have RAW expression values then also you can create co-expression matrix!
i want to create using mutual rank values from co-expression database. This is because correlation data from COEXPRESdb was clustered using Euclidean distance matrix. For which we require PCC values, but as i said latest version of COEXPRESdb gives only MR and no PRR column.
why can't you just use the MR values as a distance? It might not be subadditive