[BioC] Single sample normalization of single-channel Agilent microarrays

[Gabriele Zoppoli]

Actually, I also don't think RMA-like normalization methods, including the
fRMA, can be used for Agilent single-channel arrays


On Tue, Aug 26, 2014 at 7:25 PM, Ryan <rct at thompsonclan.org> wrote:

> Well, if you have a large training set, one option is to use frmaTools to
> generate a fRMA normalization for your dataset. Then you can use this
> normalization on the individual samples in the test/validation set.
>
> http://bioconductor.org/packages/release/bioc/html/frmaTools.html
>
> Also, I know there was another similar method for freezing normalization
> and other parameters based on a training set, but I can't remember the name
> of it at all, so I can't find it on Google.
>
>
> On Tue Aug 26 09:42:45 2014, Gabriele Zoppoli [guest] wrote:
>
>> Dear BioConductor community,
>>
>> when faced with the concept of generating a microarray-based classifier
>> for a clinical condition (say responder vs non-responder to a treatment), I
>> have issues understaing how, after a model is built from a training set, it
>> can be applied prospectively in a serial way in a prospective trial. It is
>> my understanding that most normalization methods depend, at some point, on
>> the information derived from the microarray batch which a given sample is
>> normalized with. Few methods circumvent this issue, such as fRMA (in case
>> one has the possibility to use Affy HGU133 Plus 2.0 arrays) or SCAN.UPC,
>> which would be suitable for most Affy arrays and even dual-channel Agilent
>> arrays. What about single-channel Agilent arrays? And which were the
>> methods used in all the works published before those methods were
>> published? Thanks in advance, I hope this is not too general a question
>>
>>   -- output of sessionInfo():
>>
>> R version 3.1.0 (2014-04-10)
>> Platform: x86_64-pc-linux-gnu (64-bit)
>>
>> locale:
>>   [1] LC_CTYPE=en_US.UTF-8          LC_NUMERIC=C
>> LC_TIME=de_BE.UTF-8           LC_COLLATE=en_US.UTF-8
>> LC_MONETARY=de_BE.UTF-8
>>   [6] LC_MESSAGES=en_US.UTF-8       LC_PAPER=de_BE.UTF-8
>> LC_NAME=de_BE.UTF-8           LC_ADDRESS=de_BE.UTF-8
>> LC_TELEPHONE=de_BE.UTF-8
>> [11] LC_MEASUREMENT=de_BE.UTF-8    LC_IDENTIFICATION=de_BE.UTF-8
>>
>> attached base packages:
>> [1] parallel  splines   stats     graphics  grDevices utils     datasets
>> methods   base
>>
>> other attached packages:
>>   [1] frma_1.16.0          SCAN.UPC_2.6.3       sva_3.10.0
>>  mgcv_1.8-1           nlme_3.1-117         corpcor_1.6.6
>> foreach_1.4.2
>>   [8] affyio_1.32.0        affy_1.42.3          GEOquery_2.30.1
>> oligo_1.28.2         Biostrings_2.32.1    XVector_0.4.0
>> IRanges_1.22.9
>> [15] oligoClasses_1.26.0  Biobase_2.24.0       BiocGenerics_0.10.0
>> BiocInstaller_1.14.2 xlsx_0.5.5           xlsxjars_0.6.0       rJava_0.9-6
>> [22] ggplot2_1.0.0        aod_1.3              survcomp_1.14.0
>> prodlim_1.4.3        survival_2.37-7      limma_3.20.8
>>
>> loaded via a namespace (and not attached):
>>   [1] affxparser_1.36.0     bit_1.1-12            bootstrap_2014.4
>> codetools_0.2-8       colorspace_1.2-4      DBI_0.2-7
>>  digest_0.6.4
>>   [8] ff_2.2-13             GenomeInfoDb_1.0.2    GenomicRanges_1.16.3
>> grid_3.1.0            gtable_0.1.2          iterators_1.0.7
>>  KernSmooth_2.23-12
>> [15] lattice_0.20-29       lava_1.2.6            MASS_7.3-33
>>  Matrix_1.1-4          munsell_0.4.2         plyr_1.8.1
>> preprocessCore_1.26.1
>> [22] proto_0.3-10          Rcpp_0.11.2           RCurl_1.95-4.1
>> reshape2_1.4          rmeta_2.16            scales_0.2.4
>> stats4_3.1.0
>> [29] stringr_0.6.2         SuppDists_1.1-9.1     survivalROC_1.0.3
>>  tools_3.1.0           XML_3.98-1.1          zlibbioc_1.10.0
>>
>> --
>> Sent via the guest posting facility at bioconductor.org.
>>
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>>
>


-- 
Gabriele Zoppoli, MD
Ph.D., Clinical and Experimental Oncology and Hematology
 Internal Medicine Specialist
Research Assistant, DiMI, IRCCS AOU San Martino IST, Genova, IT
Research Fellow, BCTL J.C. Heuson, Institut J. Bordet, Brussels, BE
BIG Deputy for the Gruppo Oncologico Italiano di Ricerca Clinica (GOIRC)


Tel: +39 010 353 7968
Mobile : +32 478 24 03 11
Email:            gabriele.zoppoli at unige.it
Alt. Email:     zoppoli at gmail.com
Alt. Email 2:  gabriele.zoppoli at bordet.be
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