normalize.quantiles: Quantile Normalization
In affy: Methods for Affymetrix Oligonucleotide Arrays
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Description
Using a normalization based upon quantiles, this function
normalizes a matrix of probe level intensities.
Usage
1
normalize.AffyBatch.quantiles(abatch, type=c("separate","pmonly","mmonly","together"))
Arguments
abatch
an AffyBatch object.
type
A string specifying how the normalization should be
applied. See details for more.
Details
This method is based upon the concept of a quantile-quantile
plot extended to n dimensions. No special allowances are made for
outliers. If you make use of quantile normalization either through
rma or expresso
please cite Bolstad et al, Bioinformatics (2003).
The type argument should be one of
"separate","pmonly","mmonly","together" which indicates whether
to normalize only one probe type (PM,MM) or both together or separately.
Value
A normalized AffyBatch.
Author(s)
Ben Bolstad, bmbolstad.com
References
Bolstad, B (2001) Probe Level Quantile Normalization of High Density
Oligonucleotide Array Data. Unpublished manuscript
http://bmbolstad.com/stuff/qnorm.pdf
Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P. (2003)
A Comparison of Normalization Methods for High Density
Oligonucleotide Array Data Based on Bias and Variance.
Bioinformatics 19(2) ,pp 185-193. http://bmbolstad.com/misc/normalize/normalize.html
See Also
affy documentation built on Nov. 8, 2020, 8:18 p.m.
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Description Usage Arguments Details Value Author(s) References See Also
Description
Using a normalization based upon quantiles, this function normalizes a matrix of probe level intensities.
Usage
1 | normalize.AffyBatch.quantiles(abatch, type=c("separate","pmonly","mmonly","together"))
|
Arguments
abatch |
an |
type |
A string specifying how the normalization should be applied. See details for more. |
Details
This method is based upon the concept of a quantile-quantile
plot extended to n dimensions. No special allowances are made for
outliers. If you make use of quantile normalization either through
rma or expresso
please cite Bolstad et al, Bioinformatics (2003).
The type argument should be one of
"separate","pmonly","mmonly","together" which indicates whether
to normalize only one probe type (PM,MM) or both together or separately.
Value
A normalized AffyBatch.
Author(s)
Ben Bolstad, bmbolstad.com
References
Bolstad, B (2001) Probe Level Quantile Normalization of High Density Oligonucleotide Array Data. Unpublished manuscript http://bmbolstad.com/stuff/qnorm.pdf
Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P. (2003) A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance. Bioinformatics 19(2) ,pp 185-193. http://bmbolstad.com/misc/normalize/normalize.html
See Also
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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