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Implement DESeq2 like normalization #22

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@lpantano

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@lpantano

Add the code that from a count matrix, can get the size factor to normalize the data.

So, input would be: count data and output: normalized count data.

In R the code is like this:

loggeomeans <- rowMeans(log(counts))
sf <- apply(counts, 2, function(cnts) {
      exp(median((log(cnts) - loggeomeans)[is.finite(loggeomeans) & cnts > 0]))
    })
sf <- sf/exp(mean(log(sf)))
t(t(counts)/sf)

This code can be inside libs/math.py

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