Description Usage Arguments Value See Also Examples
Apply sum normalization to a matrix or poplin object. For each sample, feature intensities are divided by the sum of all intensity values.
1 2 3 4 5  | ## S4 method for signature 'matrix'
normalize_sum(x, restrict = FALSE, rescale = FALSE)
## S4 method for signature 'poplin'
normalize_sum(x, xin, xout, restrict = FALSE, rescale = FALSE)
 | 
x | 
 A matrix or poplin object.  | 
restrict | 
 Logical controlling whether any feature with missing values is excluded from the calculation of normalization factors.  | 
rescale | 
 Logical controlling whether the normalized intensities are multiplied by the median of normalization factors to make look similar to their original scales.  | 
xin | 
 Character specifying the name of data to retrieve from   | 
xout | 
 Character specifying the name of data to store in   | 
A matrix or poplin object of the same dimension as
x containing the normalized intensities.
Other normalization methods: 
normalize_cyclicloess(),
normalize_mad(),
normalize_mean(),
normalize_median(),
normalize_pqn(),
normalize_scale(),
normalize_vsn(),
poplin_normalize()
1 2 3 4 5 6 7 8  | data(faahko_poplin)
## poplin object
normalize_sum(faahko_poplin, xin = "knn", xout = "knn_sum")
## matrix
m <- poplin_data(faahko_poplin, "knn")
normalize_sum(m, rescale = TRUE)
 | 
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