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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
libs/math.py
The text was updated successfully, but these errors were encountered:
Is this count matrix the one created in gff/convert.py ? (example file at data/examples/gff/gff_tsv_expression_counts.tsv)
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Hi! This would be to do an extra step from that matrix. So, the idea is once you have the matrix, apply this calculation to get a normalize one.
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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:
This code can be inside
libs/math.py
The text was updated successfully, but these errors were encountered: