Difference between revisions of "Agilent normalization (analysis)"
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− | :[[File: | + | :[[File:Microarray-normalization-Agilent-normalization-icon.png]] Agilent normalization |
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+ | :{{Class|ru.biosoft.analysis.AgilentNormalization}} | ||
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:[[Ru.biosoft.analysis (plugin)|ru.biosoft.analysis (Common methods of data analysis plug-in)]] | :[[Ru.biosoft.analysis (plugin)|ru.biosoft.analysis (Common methods of data analysis plug-in)]] | ||
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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 | + | 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
- 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
- GK Smyth and TP Speed (2003). Normalization of cDNA microarray data. Methods 31, 265-273.