[BioC] Using limma for quantitative proteomics data

[Richard Friedman]

Dear Yong,

	It would be helpful if you could say something about the method
used to identify differentially expressed proteins from quantitative  
proteomics data.
Is it a protein microarray - if so which platform.
Is it mass spec?
I would think, and somebody please correct me if I am wrong,
that continuous protein data could be analyzed similarly to contnuous
mRNA data as far as differential expression goes - although  
preprocessing
might be signficantly different. For example. I am currently analyzing
a JPT peptide array and I am doing the preprocessing with Rapmad
and the differential expression with Limma.

with hopes that this helps,
Rich

On Jun 19, 2012, at 3:39 PM, Yong Li 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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