rankZ: Rank Z transformation
In DOQTL: Genotyping and QTL Mapping in DO Mice
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
This is also called the inverse normal transformation. We rank the data in x, divide by n-1, and take quantiles from the normal distribution using qnorm.
Usage
1
rankZ(x)
Arguments
x
Numeric vector of values to be transformed.
Details
We often use this when there are hundreds or thousands of phenotypes. This allows us to calculate permutation derived thresholds once and use them for all phenotypes.
Value
Numeric vector with a normal distribution.
Author(s)
Daniel Gatti
Examples
1
DOQTL documentation built on May 6, 2019, 3:09 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
This is also called the inverse normal transformation. We rank the data in x, divide by n-1, and take quantiles from the normal distribution using qnorm.
Usage
1 | rankZ(x)
|
Arguments
x |
Numeric vector of values to be transformed. |
Details
We often use this when there are hundreds or thousands of phenotypes. This allows us to calculate permutation derived thresholds once and use them for all phenotypes.
Value
Numeric vector with a normal distribution.
Author(s)
Daniel Gatti
Examples
1 |
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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