I have a table of genomic data. The rows are the patients, the columns are the genes and the entries are the gene abundances. I need to binarize the data so that above a threshold the entries are substituted by 1's and below the threshold, the entries are substituted by 0's. Which is the best way to do this? How do I find the correct threshold?
I need to binarize the data to obtain the correspondent biadjacency matrix of an unweighted network. Thank you for your help.
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written
by
mirko.hu •
2 answers
One way to do it is with sklearn. Don't know if that's the best way.
How do I find the correct threshold?
This can vary for each patient, depending on the heterogeneity in your cohort. IMO, it's hard to find one threshold for all samples/genes. What you can do is
- add quartiles to all genes in each patient
- Take 3rd and 4th quartiles as 1 and rest 0 for each patient
You can do it basic R/python skills.
P.S: Not sure what your goals are, the answer is just to let you know how to do it. How much sense it makes sense biologically is up to you.
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