meanNormalization: Intensity of each variable in a given sample is divided by...
In ComputationalProteomics/NormalyzerDE: Evaluation of normalization methods and calculation of differential expression analysis statistics
meanNormalization R Documentation
Intensity of each variable in a given sample is divided by the mean of sum of
intensities of all variables in the sample and then multiplied by the mean
of sum of intensities of all variables in all samples. The normalized data
is then transformed to log2.
Description
Intensity of each variable in a given sample is divided by the mean of sum of
intensities of all variables in the sample and then multiplied by the mean
of sum of intensities of all variables in all samples. The normalized data
is then transformed to log2.
Usage
meanNormalization(rawMatrix, noLogTransform = FALSE)
Arguments
rawMatrix
Target matrix to be normalized
noLogTransform
Assumes no need for log transformation
Value
Normalized and log-transformed matrix
Examples
data(example_data_only_values_small)
normMatrix <- meanNormalization(example_data_only_values)
ComputationalProteomics/NormalyzerDE documentation built on Oct. 18, 2024, 9:57 p.m.
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| meanNormalization | R Documentation |
Intensity of each variable in a given sample is divided by the mean of sum of intensities of all variables in the sample and then multiplied by the mean of sum of intensities of all variables in all samples. The normalized data is then transformed to log2.
Description
Intensity of each variable in a given sample is divided by the mean of sum of intensities of all variables in the sample and then multiplied by the mean of sum of intensities of all variables in all samples. The normalized data is then transformed to log2.
Usage
meanNormalization(rawMatrix, noLogTransform = FALSE)
Arguments
rawMatrix |
Target matrix to be normalized |
noLogTransform |
Assumes no need for log transformation |
Value
Normalized and log-transformed matrix
Examples
data(example_data_only_values_small)
normMatrix <- meanNormalization(example_data_only_values)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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