Difference between revisions of "Agilent normalization (analysis)"

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For analyzing single-channel information rather than differential expression based on log-ratios, the data should be normalized using a single channel-normalization technique. Single channel normalization uses further options of the <code>normalizeBetweenArrays</code> function.
 
For analyzing single-channel information rather than differential expression based on log-ratios, the data should be normalized using a single channel-normalization technique. Single channel normalization uses further options of the <code>normalizeBetweenArrays</code> function.
  
For the detailed description of the LIMMA functions see the [http://www.bioconductor.org/packages/2.7/bioc/vignettes/limma/inst/doc/usersguide.pdf LIMMA user’s guide].
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For the detailed description of the LIMMA functions see the [http://www.bioconductor.org/packages/2.7/bioc/vignettes/limma/inst/doc/usersguide.pdf LIMMA user�s guide].
  
 
'''Note''': Before the Agilent Normalization is started you need to install R and Rserve on your computer. For more information on installing, please visit [http://www.r-project.org/ R-project website].
 
'''Note''': Before the Agilent Normalization is started you need to install R and Rserve on your computer. For more information on installing, please visit [http://www.r-project.org/ R-project website].
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Latest revision as of 18:15, 9 December 2020

Analysis title
Microarray-normalization-Agilent-normalization-icon.png Agilent normalization
Provider
Institute of Systems Biology
Class
AgilentNormalization
Plugin
ru.biosoft.analysis (Common methods of data analysis plug-in)

[edit] Agilent Normalization

Normalization of Agilent files based on the functions of the Bioconductor LIMMA package.

Smyth and Speed1 give an overview of the normalization techniques implemented in these functions.

Usually data from spotted microarrays will be normalized using the function normalizeWithinArrays. A minority of data will also be normalized using normalizeBetweenArrays if diagnostic plots suggest a difference in scale between the arrays:

  • normalizeWithinArrays - normalize the expression log-ratios for one or more two-color spotted microarray experiments so that the log-ratios average to zero within each array or sub-array;
  • normalizeBetweenArrays - normalizes expression intensities so that the intensities or log-ratios have similar distributions across a set of arrays.

For analyzing single-channel information rather than differential expression based on log-ratios, the data should be normalized using a single channel-normalization technique. Single channel normalization uses further options of the normalizeBetweenArrays function.

For the detailed description of the LIMMA functions see the LIMMA user�s guide.

Note: Before the Agilent Normalization is started you need to install R and Rserve on your computer. For more information on installing, please visit R-project website.

Note: Duplicated identifiers will be modified.

[edit] References

  1. GK Smyth and TP Speed (2003). Normalization of cDNA microarray data. Methods 31, 265-273.
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