Thank you for your reply. actually I have two biological replicates in my  experiment, and I'm confident with the statistic power of limma  with your information. 


gang jiang




At 2011-05-17 00:15:14，"Naomi Altman" <naomi@stat.psu.edu> wrote:

>If you have biological replicates, then using LIMMA is preferred with 
>small sample sizes.  If you have only technical replicates, then you 
>really cannot do a proper statistical analysis of the data.  Since 
>you have a disconnected design, you might use separate channel 
>analysis to simplify the comparisons you want to make.
>
>Regards,
>Naomi Altman
>
>
>At 07:40 AM 5/16/2011, =?GBK?B?va241Q==?= wrote:
>>Hello Everyone!
>>
>>
>>I'm now working with my expression microarray data by limma to 
>>detect differential expression probes. I have biology as my 
>>knowledge background ,not statistics, so I'm confused with the 
>>design matrix and contrast matrix in the limma usersguide.  now i 
>>have read the target file
>>as follows:
>>SlideNumber   FileName Cy3 Cy5
>>1           1       15_1_3.txt  BI  BM
>>2           2       15_1_4.txt  BM  BI
>>3           3       18_1_2.txt BI2 BM2
>>4           4       18_1_3.txt BM2 BI2
>>5           5       16_1_1.txt BE2 BM2
>>6           6       16_1_2.txt BM2 BE2
>>
>>
>>because there is no connection from BI(or BM) to the other samples, 
>>dose that mean I have to contrast the differences(BI-BM, BI2-BM2, 
>>BE2-BM2, BE2-BI2) separately?
>>Though I read the linear models and Empirical Bayes Methods theory 
>>carefully, I only know little.  I wonder It is proper to detect 
>>differential expression by limma when there are only two replicates?
>>
>>
>>
>>
>>
>>
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>>
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>
>
>

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