[BioC] limma advice required. Investigating the amplification of small sample RNA
a.mcdonagh at imperial.ac.uk
Wed Jul 26 16:51:06 CEST 2006
Gordon, thanks for the reply.
I am a little confused. How can I fit contrasts if the design (not mine
btw) is unconnected? As far as I can see, the hybridizations are
anlagous to those shown on page 48 of the limma guide, the section that
deals with single channel analysis. Note the column names of my MA object
There are no biological replicates. The experiment was performed by
taking a pool of total RNA from C0- and C60- samples. The amount of RNA
was estimated for each, and dilutions were made of the C0- and C60-
total RNA. These dilutions, have artificially low total RNA (as you
might get from some tissue biopsy). These samples were subjected to
either 1 round (cohybe C0- and C60- on slides 1,3) or 2 rounds (cohybe
C0- and C60- on slides 2,4) of amplification. The total RNA samples were
hybridized on slides 5 and 6.
C0-.round1 <-----> C60-.round1
If I create this design matrix:
round_1 round_2 non_amp
1 1 0 0
2 0 1 0
3 -1 0 0
4 0 -1 0
5 0 0 1
6 0 0 -1
Then I have the log ratios of sample C60 and C0 for each protocol. But I
want to compare round_1 v non_amp and round_2 v non_amp to see if they
are significantly different. I am interested to see which genes show
significantly different log ratios. In this case, you suggest fitting
the contrasts. So, I did the following to estimate the difference in log
> as.matrix(hyp.design) %*% as.matrix(cont.one.non)
How does this help me?
Gordon K Smyth wrote:
>On Wed, July 26, 2006 8:47 pm, Andrew Mcdonagh wrote:
>>Thanks for getting back to me, although I don't think you answered my
>>question. On the surface it looks like another couple of posts relating
>>to this, but that's not actually the case
>>I think I might not have explained myself clearly. I have read the limma
>>guide, and I can see how you calculate the t-statistics on the
>>coefficients. The example that you give is relevant to me if the
>>coefficients themselves are comparisons between protocols. Clearly from
>>my design matrix the effect is not a comparison of protocols. So the
>>three coefficients that I estimate are the effect of protocol 1,
>>protocol 2 and protocol 3.
>Use contrasts.fit to make the coefficients the comparisons you want.
>>Also, the question about single channel analysis relates to this. Do you
>>have any suggestions
>Please send questions to the Bioconductor list.
More information about the Bioconductor