[BioC] two color arrays normalization

Giusy Della Gatta Gatta at icg.cpmc.columbia.edu
Wed Feb 11 16:31:53 CET 2009


Hi Naomi,

I studied the model matrix command and it seems
that is the one that I need to construct a new matrix
and specify which will be my reference.

>From LIMMA user's guide is not clear when I have to use
this command.
In the guide I found this example: It is a two-color microarray experiments in which
a common reference has been used on all the arrays (I have exactly 
this kind of experiment):


> targets <- readTargets("runxtargets.txt")
> targets
   SlideNumber       Cy3       Cy5
1         2144      EGFP      AML1
2         2145      EGFP      AML1
3         2146      AML1      EGFP
4         2147      EGFP AML1.CBFb
5         2148      EGFP AML1.CBFb
6         2149 AML1.CBFb      EGFP
7         2158      EGFP      CBFb
8         2159      CBFb      EGFP
9         2160      EGFP AML1.CBFb
10        2161 AML1.CBFb      EGFP
11        2162      EGFP AML1.CBFb
12        2163 AML1.CBFb      EGFP
13        2166      EGFP      CBFb
14        2167      CBFb      EGFP
> design <- designMatrix(targets,ref="EGFP")
> design
   AML1 AML1.CBFb CBFb
1     1         0    0
2     1         0    0
3    -1         0    0
4     0         1    0
5     0         1    0
6     0        -1    0
7     0         0    1
8     0         0   -1
9     0         1    0
10    0        -1    0
11    0         1    0
12    0        -1    0
13    0         0    1
14    0         0   -1

> fit <- lmFit(RG, design)


in this way the specific matrix is constructed, but why I have to use the 
"fit<- lmfit" command?

And also, after this command can I go ahead with my analysis that will consist in:

-background correction
-MA<-normalizeWithinArrays(RG, method="loess")
- MA<-normalizeBetweenArrays(MA, method="Rquantile")
-lm<-lmFit(MA,design=design,ndups=1,spacing=1,block=NULL,correlation,weights=NULL,method="ls")
-decideTests(lm,method="separate",adjust.method="BH",p.value=0.05,lfc=0)
> Dt<-decideTests(lm,method="separate",adjust.method="BH",p.value=0.05,lfc=0)
> d1 <- ebayes(lm)


Thank you very much for your help
Giusy
-----Original Message-----
From: Naomi Altman [mailto:naomi at stat.psu.edu]
Sent: Tue 2/10/2009 11:33 AM
To: Giusy Della Gatta; Naomi Altman
Cc: bioconductor at stat.math.ethz.ch
Subject: RE: [BioC] two color arrays normalization
 
Dear Giusy,
Please keep the discussion on the list.

I have forgotten some of the specifics of the code, so I am going to 
turn this over to someone else to respond.

--Naomi

At 11:19 AM 2/10/2009, Giusy Della Gatta wrote:
>Hi Naomi only another question,
>at this point I am wondering why I need the "Target file"
>(see in attachment)?
>I was sure that by composing this file was automatic the recognition
>of my reference and my treatment signals.
>
>Thank you
>Giusy
>
>
>-----Original Message-----
>From: Naomi Altman [mailto:naomi at stat.psu.edu]
>Sent: Tue 2/10/2009 8:33 AM
>To: Giusy Della Gatta; Naomi Altman
>Cc: bioconductor at stat.math.ethz.ch
>Subject: RE: [BioC] two color arrays normalization
>
>This will make no difference to the statistical tests and
>p-values.  The simplest ways to get the M values right are:
>
>Either: Create the design matrix as in the limma manual - say
>designMatrix. Then switch sign.
>
>designMatrix= - designMatrix
>
>Then proceed as in the manual.
>
>Or: Create the design matrix and do the analysis (without switching
>sign).  Call the output fit.out.
>The M-values are in fit.out$coef.
>
>fit.out$coef= - fit.out$coef
>
>
>
>
>
>
>At 10:32 PM 2/9/2009, Giusy Della Gatta wrote:
> >Hi Naomi,
> >my colleague told me that in the calculation of the M value
> >the green channel is used as reference by default.
> >You can see it also by considering the corrispondent formula:
> >(M = log(R/G) = log R - log G).
> >
> >In my  experiment, the red color is the reference
> >so I was thinking that in this case I have to use some
> >specific command to invert the M formula?
> >
> >Thank you!
> >Giusy
> >
> >-----Original Message-----
> >From: Naomi Altman [mailto:naomi at stat.psu.edu]
> >Sent: Mon 2/9/2009 9:56 PM
> >To: Giusy Della Gatta; bioconductor at stat.math.ethz.ch
> >Subject: Re: [BioC] two color arrays normalization
> >
> >If there is no dye-swap, then what do you mean by "swapping of the colors"?
> >
> >--Naomi
> >
> >At 07:56 PM 2/9/2009, Giusy Della Gatta wrote:
> >
> > >Hi everybody,
> > >
> > >I am analyzing two color Agilent microarrays
> > >by using LIMMA package.
> > >In my specific case the red channel is representing
> > >"the reference" while the green channel is "the treatment".
> > >Is it enough to use the Target File composition to specify the name
> > >of  the samples
> > >and their corrispondet channels?  Or I have to use other specific commands
> > >to specify the "swapping" of the colors?
> > >
> > >Thank you in advance!
> > >Regards
> > >Giusy
> > >
> > >_______________________________________________
> > >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
> >
> >Naomi S. Altman                                814-865-3791 (voice)
> >Associate Professor
> >Dept. of Statistics                              814-863-7114 (fax)
> >Penn State University                         814-865-1348 (Statistics)
> >University Park, PA 16802-2111
>
>Naomi S. Altman                                814-865-3791 (voice)
>Associate Professor
>Dept. of Statistics                              814-863-7114 (fax)
>Penn State University                         814-865-1348 (Statistics)
>University Park, PA 16802-2111
>
>
>

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111



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