[BioC] Using limma for quantitative proteomics data

[axel.klenk at actelion.com]

Dear Yong,

I don't think you need an MAList -- all limma functions will accept a 
simple matrix
of your log2 ratios... or at least, all limma functions I have ever used, 
will do that... :-)

Cheers,

 - axel


Axel Klenk
Research Informatician
Actelion Pharmaceuticals Ltd / Gewerbestrasse 16 / CH-4123 Allschwil / 
Switzerland




From:
Yong Li <mail.yong.li at googlemail.com>
To:
bioconductor at r-project.org
Date:
26.06.2012 00:01
Subject:
Re: [BioC] Using limma for quantitative proteomics data
Sent by:
bioconductor-bounces at r-project.org



Dear Aaron,

thank you and others for suggestions. My data is really ratios and not
absolute values for normal and tumor. Sorry that I am still not quite
sure how to move forward with limma when I take log2 of the ratios. It
looks like I then will have the M component of the MAList, but how can
I construct the A to make an MAList? Or I am missing something here?

Kind regards,
Yong

On Tue, Jun 19, 2012 at 11:09 PM, Aaron Mackey <amackey at virginia.edu> 
wrote:
> There's a thread on the bioconductor mailing list about using voom for
> RSEM-based RNA-seq quantification, in which  Gordon Smythe explained 
that
> while voom() was designed for count data, it doesn't require it.  As Tim
> Triche has suggested, if you're raw data is really ratios (and not 
absolute
> values for normal and tumor), then you should take log2 of those ratios 
and
> use limma from there; you can then also hijack the arrayQualityMetrics
> package to check QC (MA plots, mean-variance relationships, etc.)
>
> -Aaron
>
> On Tue, Jun 19, 2012 at 3:39 PM, Yong Li <mail.yong.li at googlemail.com>
> wrote:
>>
>> Dear Aaron,
>>
>> thank you for your quick answer! I have checked the help page of
>> voom() but it seems to be used for count data. My data are just
>> tumor/normal ratios. I am wondering if you could provide more details?
>>
>> Best regards,
>> Yong
>>
>> On Tue, Jun 19, 2012 at 8:18 PM, Aaron Mackey <amackey at virginia.edu>
>> wrote:
>> > yes, it should be possible with a voom()-based analysis to get the
>> > variances
>> > "right".
>> >
>> > -Aaron
>> >
>> > On Tue, Jun 19, 2012 at 12:47 PM, Yong Li 
<mail.yong.li at googlemail.com>
>> > wrote:
>> >>
>> >> Hello,
>> >>
>> >> limma has been so valuable in microarray data analysis, but has 
anyone
>> >> used limma for finding differentially expressed proteins from
>> >> quantitative proteomics data? The data I got has tumor/normal ratios
>> >> of thousands proteins, and both tumor and normal have a number of
>> >> replicates. Could such data be analyzed with limma?
>> >>
>> >> If limma can not be used here, what statistics method is suitable so
>> >> that we can get statistically significant proteins with p-values? 
Any
>> >> suggestion is appreciated.
>> >>
>> >> Kind regards,
>> >> Yong
>> >>
>> >> _______________________________________________
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>> >
>> >
>>
>> _______________________________________________
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>
>

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