Question: About between-array normalization in limma
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gravatar for De-Jian ZHAO
12.1 years ago by
De-Jian ZHAO240
De-Jian ZHAO240 wrote:
Hi,everyone. I am now analyzing my microarray data using limma. I am not sure when to use between-array normalization. In the first case of chapter 11 in limma user's guide, it is mentioned that between-array normalization is not routine and should only be done when there is good evidence. I wonder what is a good evidence and whether I should carry out between-array normalization in my data. See the attachment for the boxplot. In the attached boxplot,the blue, red, and green ones stand for three different hybridization groups. There are 6 replications in each group. I want to carry out between-array normalization in the three groups respectively and then combine them together to fit a linear model. Is this reasonable? In my opinion, we can always carry out between-array normalization between the replications of the same hybridization group (unless there is dye swap). Thanks in advance for your reply. Dejian Zhao
ADD COMMENTlink modified 12.1 years ago by Simon Lin270 • written 12.1 years ago by De-Jian ZHAO240
Answer: About between-array normalization in limma
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gravatar for Sean Davis
12.1 years ago by
Sean Davis21k
United States
Sean Davis21k wrote:
De-Jian,ZHAO wrote: > Hi,everyone. > > I am now analyzing my microarray data using limma. I am not sure > when to use between-array normalization. > > In the first case of chapter 11 in limma user's guide, it is > mentioned that between-array normalization is not routine and should > only be done when there is good evidence. I wonder what is a good > evidence and whether I should carry out between-array normalization > in my data. See the attachment for the boxplot. > > In the attached boxplot,the blue, red, and green ones stand for > three different hybridization groups. There are 6 replications in > each group. I want to carry out between-array normalization in > the three groups respectively and then combine them together to fit > a linear model. Is this reasonable? In my opinion, we can always > carry out between-array normalization between the replications of > the same hybridization group (unless there is dye swap). The rule-of-thumb is that if you are working with two-color data and using ratios only, then you probably do not need between-array normalization. If you want to do single-channel analyses of two-color data or are using single-channel data (affy, etc.), then you need to use between-array normalization. The other rule-of-thumb with normalization is to do the least reasonable amount possible. So, despite the fact that one _can_ do between-array normalization, one should not do it unless there is a good evidence that it is important, after looking at within-array normalization results. Sean
ADD COMMENTlink written 12.1 years ago by Sean Davis21k
Answer: About between-array normalization in limma
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gravatar for Simon Lin
12.1 years ago by
Simon Lin270
Simon Lin270 wrote:
Sean Davis Wrote: >The rule-of-thumb is that if you are working with two-color data and >using ratios only, then you probably do not need between-array >normalization. What is the rationale behind this claim? Is it because the common ref channel serves as kind of internal calibration control already? Seems that the current recommendation of normalization is on the less agreesive side? -Simon
ADD COMMENTlink written 12.1 years ago by Simon Lin270
Dear Simon, On Wednesday 24 October 2007 02:32, Simon Lin wrote: > Sean Davis Wrote: > >The rule-of-thumb is that if you are working with two-color data and > >using ratios only, then you probably do not need between-array > >normalization. > > What is the rationale behind this claim? Is it because the common ref > channel serves as kind of internal calibration control already? > I think (at least part of) the argument had to do with the variance- bias trade-off. And I think the NAR paper by Dudoit et al. on normalization had some comments regarding these issues (though that paper is a few years old by now). I think I also remember seening a pdf of a talk by K. Kerr and colleagues where these issues might have been addressed (though I am not sure). Anyway, I'm also interested in knowing if there are stronger arguments and more recent studies. Best, R. > Seems that the current recommendation of normalization is on the less > agreesive side? > > -Simon > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Ram?n D?az-Uriarte Statistical Computing Team Centro Nacional de Investigaciones Oncol?gicas (CNIO) (Spanish National Cancer Center) Melchor Fern?ndez Almagro, 3 28029 Madrid (Spain) Fax: +-34-91-224-6972 Phone: +-34-91-224-6900 http://ligarto.org/rdiaz PGP KeyID: 0xE89B3462 (http://ligarto.org/rdiaz/0xE89B3462.asc) **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y ...{{dropped:3}}
ADD REPLYlink written 12.1 years ago by Ramon Diaz1.1k
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