[BioC] presence/absence call using oligo array?

[xpeng]

I agree. Thanks a lot.

Even I want to find differentially expressed genes. How do I normalize? The 
oligos are designed based on parasite genes, while samples from uninfected 
tissue have no parasite RNAs.

Best,
Xinxia

>===== Original Message From Sean Davis <sdavis2 at mail.nih.gov> =====
>On 1/13/06 3:07 AM, "xpeng" <xpeng at utk.edu> wrote:
>
>> Dear Bioc,
>>
>> Has someone ever used long oligo arrays to test if genes were expressed or
>> not? I have two microarray slides on which oligonucleotides (65mer) for 
genes
>> from a parasite genome were spotted. One gene has one oligo but spotted 
twice
>> on each array. One slide has a RNA sample extracted from infected tissues
>> (therefore mixture of both parasite RNAs and RNAs from host tissues)
>> co-hybridized with RNAs from uninfected host tissue (no parasite RNAs).
>> Another is a biological replicate but with dye-swap. People want to know 
what
>> parasite genes are expressed in the infected tissue. Is it possible to do 
so?
>> Related publications are highly appreciated.
>
>You cannot answer that DIRECTLY with this design, I don't think.  You could
>look for differential expression between the two samples--that is probably
>as close as you can get.  You can perhaps say what genes are NOT expressed,
>as those spots will have very low intensity (within the range of
>background), but that doesn't imply that the others are expressed.  And, you
>might think that all genes that show some signal AND are differentially
>expressed between the two samples would be expressed parasite genes, but
>these could also be due to regulation of the genes in the infected host
>combined with some cross-hybridization.  So, I would look for
>differentially-expressed genes and see what that can tell you.  With only
>two samples, doing meaningful statistics will be difficult, but you could
>try using limma or some other moderated testing procedure designed for small
>samples (and able to account for your replicated probes).  Alternatively,
>just rank the genes by fold change.  In the end, if you REALLY want to know
>which genes are differentially expressed, another couple of arrays would
>probably help.
>
>Sean
>
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