medianNormalization: Intensity of each variable in a given sample is divided by...
In NormalyzerDE: Evaluation of normalization methods and calculation of differential expression analysis statistics
Description
Usage
Arguments
Value
Examples
Description
Intensity of each variable in a given sample is divided by the median of
intensities of all variables in the sample and then multiplied by the mean
of median of sum of intensities of all variables in all samples.
The normalized data is then log2-transformed.
Usage
1
medianNormalization(rawMatrix, noLogTransform = FALSE)
Arguments
rawMatrix
Target matrix to be normalized
noLogTransform
Assumes no need for log transformation
Value
Normalized and log-transformed matrix
Examples
1
2
data(example_data_only_values_small)
normMatrix <- medianNormalization(example_data_only_values)
NormalyzerDE documentation built on Nov. 8, 2020, 8:22 p.m.
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.
Description Usage Arguments Value Examples
Description
Intensity of each variable in a given sample is divided by the median of intensities of all variables in the sample and then multiplied by the mean of median of sum of intensities of all variables in all samples. The normalized data is then log2-transformed.
Usage
1 | medianNormalization(rawMatrix, noLogTransform = FALSE)
|
Arguments
rawMatrix |
Target matrix to be normalized |
noLogTransform |
Assumes no need for log transformation |
Value
Normalized and log-transformed matrix
Examples
1 2 | data(example_data_only_values_small)
normMatrix <- medianNormalization(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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.