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

Gabriele Zoppoli zoppoli at gmail.com
Wed Aug 27 10:45:25 CEST 2014


That is cool advice!

Thanks


On Wed, Aug 27, 2014 at 1:46 AM, Ryan <rct at thompsonclan.org> wrote:

> Yes, of course you are right about that. I should have spoken more
> generally about normalizing your training set and then normalizing each
> test/validation sample individually to the already-normalized training set.
> I think this approach is perfectly valid as long as you do not make any use
> of the clinical condition in the normalization step. For example, if you
> normalized your training set to each other using quantile normalization,
> you could save the resulting quantiles as a reference and then normalize
> each test/validation sample to those exact reference quantiles.
>
>
> On Tue Aug 26 13:51:58 2014, Gabriele Zoppoli wrote:
>
>> 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
>> <mailto: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
>>
>>     <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
>>         <http://bioconductor.org>.
>>
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>> conductor
>>
>>         <http://news.gmane.org/gmane.science.biology.informatics.
>> conductor>
>>
>>
>>
>>
>> --
>> 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 <mailto:gabriele.zoppoli at unige.it>
>> Alt. Email: zoppoli at gmail.com <mailto:zoppoli at gmail.com>
>> Alt. Email 2: gabriele.zoppoli at bordet.be
>> <mailto:gabriele.zoppoli at bordet.be>
>>
>> ----------------------------------------------------------
>>
>> Ζεῦ πάτερ ἀλλὰ σὺ ῥῦσαι ὑπ' ἠέρος υἷας Ἀχαιῶν,
>>
>> ποίησον δ' αἴθρην, δὸς δ' ὀφθαλμοῖσιν ἰδέσθαι:
>>
>> ἐν δὲ φάει καὶ ὄλεσσον, ἐπεί νύ τοι εὔαδεν οὕτως.
>>
>> /Father Zeus, at least deliver the sons of Acheans from the gloom,/
>> /And make clear the air, and give it to our eyes to see./
>> /In the light destroy us, since to do thus pleases you. (Il. 17, 645-7)
>>
>> /
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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
----------------------------------------------------------


Ζεῦ πάτερ ἀλλὰ σὺ ῥῦσαι ὑπ' ἠέρος υἷας Ἀχαιῶν,

ποίησον δ' αἴθρην, δὸς δ' ὀφθαλμοῖσιν ἰδέσθαι:

ἐν δὲ φάει καὶ ὄλεσσον, ἐπεί νύ τοι εὔαδεν οὕτως.
*Father Zeus, at least deliver the sons of Acheans from the gloom,*
*And make clear the air, and give it to our eyes to see.*

*In the light destroy us, since to do thus pleases you. (Il. 17, 645-7)*


----------------------------------------------------------

CONFIDENTIALITY NOTICE\ \ This e-mail message is intende...{{dropped:14}}



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