z.norm: Z-score normalization
In jmonlong/PopSV: Population-based detection of structural variants from Read-Depth signal
Description
Usage
Arguments
Value
Author(s)
Description
The Z-score is normalized to ensure centered distribution and similar variance across different GC classes. This is usually not necessary when the quality is comparable across the samples. However if some samples contain experiment-specific biases this approach can reduce false calls.
Usage
1
z.norm(z.df, gc.df, class.size = 5000)
Arguments
z.df
a data.frame with the Z-scores.
gc.df
a data.frame with the GC content.
class.size
the number of bins in each GC classes. Default is 5000.
Value
a vector with the normalized Z-scores.
Author(s)
Jean Monlong
jmonlong/PopSV documentation built on Sept. 15, 2019, 9:29 p.m.
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Description Usage Arguments Value Author(s)
Description
The Z-score is normalized to ensure centered distribution and similar variance across different GC classes. This is usually not necessary when the quality is comparable across the samples. However if some samples contain experiment-specific biases this approach can reduce false calls.
Usage
1 | z.norm(z.df, gc.df, class.size = 5000)
|
Arguments
z.df |
a data.frame with the Z-scores. |
gc.df |
a data.frame with the GC content. |
class.size |
the number of bins in each GC classes. Default is 5000. |
Value
a vector with the normalized Z-scores.
Author(s)
Jean Monlong
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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