Hi All,
I am in need of some basic 2-color (cDNA) microarray help.
With 3-biological replicates (one of them is a dye-swap), I wish to
merge
ONLY the raw intensities of the 3 cDNA files. This merging should take
into
account of the dye-swap file too. Finally, it should produce an HTML
(or,
CSV) file that contains ONE raw expression against each available gene
with
the relevant annotation.
I am not confident as to how I should script it. I did go through some
packages like LIMMA, but couldn't really extract what I wanted, as
they
focus mainly on statistics for differential expression.
Thank you !
Cheers,
Santana
[[alternative HTML version deleted]]
Dear Santana
This does not really help much, because the "normalized expression"
depends on the treatment. Do both channels have the same
treatment? Is this a reference design?
Anyways, to do what you want, what I generally do is use cbind to
merge the expression values with the annotation information and
write.csv to write a comma separated table which can be read into a
spreadsheet such as Excel. I do not expect to be able to do all my
processing in R. However, some of the R gurus on the list can
probably do everything in R. I meant
to cc the list when I first wrote, and I am returning this to you.
Best of luck,
Naomi
At 04:31 AM 12/2/2008, you wrote:
>Hi Naomi,
>
>Thanks for your prompt reply !
>
>Well, I wanted to experiment something, and accordingly thought that
>I would examine the individual raw data. But I believe, I should
>follow the conventional way, atleast for the time-being.
>
>Anyways, even then I have a bit of problem.
>
>I am uncertain as to how I can have each gene's normalised
>expression along with its annotation in one file. I am able to do it
>for Affymetrix data which is not very complicated, but I'm having
>problems in trying to do it with cDNA microarrays (for 3-biological
>replicates where one of them is a dye-swap).
>
>Let's say, in a nutshell, I have already done with the following :
>
>library(arrayQuality); library(graphics); library(RColorBrewer)
>
>targets <- readTargets("target77.txt")
>
>files <- c("a.gpr", "b.gpr", "c_DyeSwap.gpr") #
>Suppose these are my files
>
>RG <- read.maimages (files,source="genepix")
>
>RG$printer <- getLayout(RG$genes) # to set
print layout
>
>RG.b <- backgroundCorrect(RG)
>
>MA.RG <- normalizeWithinArrays (RG.b)
>
><http: ma.bt="">MA.BT <- normalizeBetweenArrays (MA.RG)
>
>design <- c(1,1,-1)
>
># from here, I don't know how to move ahead that would give me a
>file (.HTML/.csv) that would contain each gene's normalised
>expression with its annotation.
>
>I would highly appreciate your suggestion(s).
>
>Thanks !!
>
>Kind regards,
>
>Santana
>= = = = = = = = =
>
>On Tue, Dec 2, 2008 at 5:43 PM, Naomi Altman
><<mailto:naomi@stat.psu.edu>naomi@stat.psu.edu> wrote:
>Are you sure you want the RAW intensities. That would mean
>unaltered data. I think you want a normalized
>mean intensity. You could do that in limma using the single channel
>analysis. Limma can produce means - not just differences.
>
>Naomi Altman
>
>
>At 11:23 PM 12/1/2008, you wrote:
>Hi All,
>
>I am in need of some basic 2-color (cDNA) microarray help.
>
>With 3-biological replicates (one of them is a dye-swap), I wish to
merge
>ONLY the raw intensities of the 3 cDNA files. This merging should
take into
>account of the dye-swap file too. Finally, it should produce an HTML
(or,
>CSV) file that contains ONE raw expression against each available
gene with
>the relevant annotation.
>
>I am not confident as to how I should script it. I did go through
some
>packages like LIMMA, but couldn't really extract what I wanted, as
they
>focus mainly on statistics for differential expression.
>
>Thank you !
>
>Cheers,
>Santana
>
> [[alternative HTML version deleted]]
>
>_______________________________________________
>Bioconductor mailing list
><mailto:bioconductor@stat.math.ethz.ch>Bioconductor@stat.math.ethz.ch
>https://stat.ethz.ch/mailman/listinfo/bioconductor
>Search the archives:
><http: news.gmane.org="" gmane.science.biology.informatics.conductor="">ht
tp://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
[[alternative HTML version deleted]]
Thanks !
Well, it is the simplest type of microarray experiment, with replicate
two-color arrays of the same two RNA sources. It has its dyes swapped
for
one of the arrays:
-------------------------------------------------------------
File cy3 cy5
-------------------------------------------------------------
a wt mu
b wt mu
c_DyeSwap mu wt
Wonder how to go for the annotated output for my gene list (before
downstream statistical analysis). User guides of LIMMA and others
mainly
focus on how to obtain statistics with regards to differential
expression et
al.
Santana
= = = = = = = = =
On Wed, Dec 3, 2008 at 3:42 AM, Naomi Altman <naomi@stat.psu.edu>
wrote:
> Dear Santana
>
> This does not really help much, because the "normalized expression"
depends
> on the treatment. Do both channels have the same treatment? Is
this a
> reference design?
>
> Anyways, to do what you want, what I generally do is use cbind to
merge the
> expression values with the annotation information and write.csv to
write a
> comma separated table which can be read into a spreadsheet such as
Excel. I
> do not expect to be able to do all my processing in R. However,
some of the
> R gurus on the list can probably do everything in R. I meant
> to cc the list when I first wrote, and I am returning this to you.
>
> Best of luck,
> Naomi
>
>
> At 04:31 AM 12/2/2008, you wrote:
>
> Hi Naomi,
>
> Thanks for your prompt reply !
>
> Well, I wanted to experiment something, and accordingly thought that
I
> would examine the individual raw data. But I believe, I should
follow the
> conventional way, atleast for the time-being.
>
> Anyways, even then I have a bit of problem.
>
> I am uncertain as to how I can have each gene's normalised
expression along
> with its annotation in one file. I am able to do it for Affymetrix
data
> which is not very complicated, but I'm having problems in trying to
do it
> with cDNA microarrays (for 3-biological replicates where one of them
is a
> dye-swap).
>
> Let's say, in a nutshell, I have already done with the following :
>
> library(arrayQuality); library(graphics); library(RColorBrewer)
>
> targets <- readTargets("target77.txt")
>
> files <- c("a.gpr", "b.gpr", "c_DyeSwap.gpr") #
Suppose
> these are my files
>
> RG <- read.maimages (files,source="genepix")
>
> RG$printer <- getLayout(RG$genes) # to set
print
> layout
>
> RG.b <- backgroundCorrect(RG)
>
> MA.RG <- normalizeWithinArrays (RG.b)
>
> MA.BT <http: ma.bt=""/> <- normalizeBetweenArrays (MA.RG)
>
> design <- c(1,1,-1)
>
> # from here, I don't know how to move ahead that would give me a
file
> (.HTML/.csv) that would contain each gene's normalised expression
with its
> annotation.
>
> I would highly appreciate your suggestion(s).
>
> Thanks !!
>
> Kind regards,
>
> Santana
> = = = = = = = = =
>
> On Tue, Dec 2, 2008 at 5:43 PM, Naomi Altman <naomi@stat.psu.edu>
wrote:
> Are you sure you want the RAW intensities. That would mean
unaltered
> data. I think you want a normalized
> mean intensity. You could do that in limma using the single channel
> analysis. Limma can produce means - not just differences.
>
> Naomi Altman
>
>
> At 11:23 PM 12/1/2008, you wrote:
> Hi All,
>
> I am in need of some basic 2-color (cDNA) microarray help.
>
> With 3-biological replicates (one of them is a dye-swap), I wish to
merge
> ONLY the raw intensities of the 3 cDNA files. This merging should
take into
> account of the dye-swap file too. Finally, it should produce an HTML
(or,
> CSV) file that contains ONE raw expression against each available
gene with
> the relevant annotation.
>
> I am not confident as to how I should script it. I did go through
some
> packages like LIMMA, but couldn't really extract what I wanted, as
they
> focus mainly on statistics for differential expression.
>
> Thank you !
>
> Cheers,
> Santana
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@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
>
[[alternative HTML version deleted]]
On Wed, Dec 3, 2008 at 3:17 AM, santana sarma <aimanusarma at="" gmail.com=""> wrote:
> Thanks !
>
> Well, it is the simplest type of microarray experiment, with
replicate
> two-color arrays of the same two RNA sources. It has its dyes
swapped for
> one of the arrays:
>
> -------------------------------------------------------------
>
> File cy3 cy5
>
> -------------------------------------------------------------
>
> a wt mu
>
> b wt mu
>
> c_DyeSwap mu wt
>
>
>
> Wonder how to go for the annotated output for my gene list (before
> downstream statistical analysis). User guides of LIMMA and others
mainly
> focus on how to obtain statistics with regards to differential
expression et
> al.
The annotation is in RG$genes. You can make a data.frame that
includes the gene annotation and your values using cbind(). Then, you
can use write.csv on that data.frame to make a text file.
Sean
> On Wed, Dec 3, 2008 at 3:42 AM, Naomi Altman <naomi at="" stat.psu.edu="">
wrote:
>
>> Dear Santana
>>
>> This does not really help much, because the "normalized expression"
depends
>> on the treatment. Do both channels have the same treatment? Is
this a
>> reference design?
>>
>> Anyways, to do what you want, what I generally do is use cbind to
merge the
>> expression values with the annotation information and write.csv to
write a
>> comma separated table which can be read into a spreadsheet such as
Excel. I
>> do not expect to be able to do all my processing in R. However,
some of the
>> R gurus on the list can probably do everything in R. I meant
>> to cc the list when I first wrote, and I am returning this to you.
>>
>> Best of luck,
>> Naomi
>>
>>
>> At 04:31 AM 12/2/2008, you wrote:
>>
>> Hi Naomi,
>>
>> Thanks for your prompt reply !
>>
>> Well, I wanted to experiment something, and accordingly thought
that I
>> would examine the individual raw data. But I believe, I should
follow the
>> conventional way, atleast for the time-being.
>>
>> Anyways, even then I have a bit of problem.
>>
>> I am uncertain as to how I can have each gene's normalised
expression along
>> with its annotation in one file. I am able to do it for Affymetrix
data
>> which is not very complicated, but I'm having problems in trying to
do it
>> with cDNA microarrays (for 3-biological replicates where one of
them is a
>> dye-swap).
>>
>> Let's say, in a nutshell, I have already done with the following :
>>
>> library(arrayQuality); library(graphics); library(RColorBrewer)
>>
>> targets <- readTargets("target77.txt")
>>
>> files <- c("a.gpr", "b.gpr", "c_DyeSwap.gpr") #
Suppose
>> these are my files
>>
>> RG <- read.maimages (files,source="genepix")
>>
>> RG$printer <- getLayout(RG$genes) # to set
print
>> layout
>>
>> RG.b <- backgroundCorrect(RG)
>>
>> MA.RG <- normalizeWithinArrays (RG.b)
>>
>> MA.BT <http: ma.bt=""/> <- normalizeBetweenArrays (MA.RG)
>>
>> design <- c(1,1,-1)
>>
>> # from here, I don't know how to move ahead that would give me a
file
>> (.HTML/.csv) that would contain each gene's normalised expression
with its
>> annotation.
>>
>> I would highly appreciate your suggestion(s).
>>
>> Thanks !!
>>
>> Kind regards,
>>
>> Santana
>> = = = = = = = = =
>>
>> On Tue, Dec 2, 2008 at 5:43 PM, Naomi Altman <naomi at="" stat.psu.edu=""> wrote:
>> Are you sure you want the RAW intensities. That would mean
unaltered
>> data. I think you want a normalized
>> mean intensity. You could do that in limma using the single
channel
>> analysis. Limma can produce means - not just differences.
>>
>> Naomi Altman
>>
>>
>> At 11:23 PM 12/1/2008, you wrote:
>> Hi All,
>>
>> I am in need of some basic 2-color (cDNA) microarray help.
>>
>> With 3-biological replicates (one of them is a dye-swap), I wish to
merge
>> ONLY the raw intensities of the 3 cDNA files. This merging should
take into
>> account of the dye-swap file too. Finally, it should produce an
HTML (or,
>> CSV) file that contains ONE raw expression against each available
gene with
>> the relevant annotation.
>>
>> I am not confident as to how I should script it. I did go through
some
>> packages like LIMMA, but couldn't really extract what I wanted, as
they
>> focus mainly on statistics for differential expression.
>>
>> Thank you !
>>
>> Cheers,
>> Santana
>>
>> [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> 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
>>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> 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
>