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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