[BioC] Robustspline and two dimentional loess for two color agilent data

samane fazeli samanefazeli at gmail.com
Fri Aug 22 07:55:51 CEST 2014

Dear Dr. Smyth,
Thank you for your reply. I am comparing within-array normalization
methods (Median, Loess, robust-spline) in Agilent data. In order to
select the best method in my data, I computed mean of variability
among replicated arrays. Based on this criteria robust-spline
outperforms loess method. This difference was significant (Wilcoxon
test, p-value<0.05). In this situation, Can I apply robust-spline
method on agilent data.

On 8/22/14, Gordon K Smyth <smyth at wehi.edu.au> wrote:
> Dear Samaneh Fazeli,
> I am guessing that this is question about
>   normalizeWithinArrays(RG, method="robustspline")
> in the limma package.  When there are no print tips, robust-spline
> normalization reduces to loess normalization.  Hence you should use:
>   normalizeWithinArrays(RG, method="loess")
> for Agilent arrays.
> Best wishes
> Gordon
>> Date: Thu, 21 Aug 2014 01:54:20 -0700 (PDT)
>> From: "Samane [guest]" <guest at bioconductor.org>
>> To: bioconductor at r-project.org, samanefazeli at gmail.com
>> Subject: [BioC] Robustspline and two dimentional loess for two color
>> 	agilent	data
>> Hi
>> Since there is no print tip in Agilent technology, Could I use
>> robust-spline and two dimensional loess on such data sets? I am
>> comparing some normalization methods on two color Agilent data; In the
>> most of times, robust-spline goes the best method based on comparison of
>> variance and ICC among replicated arrays. However I can not find lots of
>> papers which have applied these methods on Agilent data.
>> I am looking forward to hearing from u.
>> Regards,
>> Samaneh Fazeli
>> -- output of sessionInfo():
>> R
>> --
>> Sent via the guest posting facility at bioconductor.org.
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