Jim,

Thanks for your detailed explanation on this, it's really helpful. I agree
with you that the term "present/absent" might be problematic, perhaps a more
accurate term is reliable/unreliable. I am not sure I agree that the
technical and biological variability are completely confounded, it's well
randomized experiment with disease/healthy status, not something like all
disease in one day/batch/..., all healthy in another day/batch/ .... The
last two paragraphs of your email answered my question very accurately
(that's exactly what I am asking). Sorry to bother you with another
question: do you think the difference is technical or biological? In our
data, we have the same set of samples (say, 100 healthy vs. 100 disease) run
using two different batches (batch difference could be due to lots of things
like reagent, hybwash...), comparing the differential expression from one
batch to another, I found many genes that are differentially expressed in
the 1st batch that are like gene B: higher present% call in one group than
the other group. However, in the 2nd batch, I found lots of them lose the
present% difference between the two groups and also goes from differentially
expressed to non-differentially expressed (I found this for both RMA and
MAS5), which makes me wonder the differential expression in the 1st batch is
due to technical reasons, not biological reasons (since the biology of the
two batches are identical because they are from the same 200 samples).

Thanks again,

-Jun


On Fri, Sep 24, 2010 at 9:40 AM, James W. MacDonald
<jmacdon@med.umich.edu>wrote:

> Hi Jack,
>
>
> On 9/23/2010 4:45 PM, Jack Luo wrote:
>
>> Hi,
>>
>> This is a conceptual question related to microarray, instead of the usage
>> of
>> any Bioconductor package. I apologize if this bothers anyone.
>>
>> I am struggling to understand the concept of differential expression in
>> terms of its resources (whether it is technical or biological). Suppose I
>> have an experiment with two groups (healthy vs. disease) and try to find
>> some differentially expressed genes, take two genes for example, both of
>> them are differentially expressed (DE) between healthy and disease.
>>
>> Gene A has present detection call for all the samples under study (but the
>> detection call p-value in the healthy group is in the order of 1e-2 ~
>> 1e-3,
>> the detection call p-value in the disease group is much more significant
>> (say, 1e-10)).
>> Gene B has 50% present call in healthy while 100% present call in cancer.
>>
>
> First let's backtrack and talk about P/M/A calls, and what they mean. The
> statistics underlying these calls are testing whether or not the PM probes
> in aggregate appear to be different than the corresponding MM probes in a
> given probeset. Others will disagree, but I think it is incorrect to assume
> that an absent call means that the transcript being measured is absent. What
> it really means is that we cannot say that the PM probes are binding more
> transcript than the MM probes.
>
> If you make the assumption that the MM probes do a good job of measuring
> background, then the absent call really means it is absent. However, a large
> percentage of MM probes have higher fluorescence readings than the
> corresponding PM probe (it varies by chip, but is usually > 30%. You can
> check with your data to verify). In addition, the MM probe intensity will
> increase with increasing amounts of transcript. These are two of the reasons
> that Affy has abandoned the use of MM probes (more real estate on the chip
> being a third), and why very few people use MAS5 for computing expression
> values any more.
>
> So I would personally caution you against interpreting these p-values as
> indicating presence or absence of the transcript.
>
> As to your question, technical and biological variability are completely
> confounded here, so you have to set up your experiments in such a way that
> the contribution from technical variability is minimized. For instance, if
> you do all controls one day and diseased the next, you cannot possibly tell
> if any differences were due to biology or to technical differences. However,
> if you randomize sample types over days processed, then the technical
> variability (which still exists, and is confounded with biological
> variability), will tend to appear as noise, and be captured by the residual
> term.
>
> Also, in my opinion there isn't any difference between the two situations
> (assuming I understand situation B correctly). What I think you are asking
> is this; are there any substantive differences between a situation where a
> gene is apparently unexpressed in sample A but expressed to a certain degree
> in sample B and a situation where a gene is expressed in both samples, but
> at a two fold (or greater) level in B vs A.
>
> In my opinion, there is no difference between those scenarios. In each
> situation, the gene is expressed at a much lower level in one sample versus
> the other. The relative levels are unimportant, as the absolute accuracy of
> our measuring device is not good.
>
> Best,
>
> Jim
>
>
>
>> My question is what's the correct interpretation in terms of whether the
>> differential expression is due to technical or biological? Are they both
>> DE
>> due to technical, or A is DE due to biological and B is due to technical,
>> or
>> they are both DE due to biological?
>>
>> Thanks a bunch,
>>
>> -Jack
>>
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>>
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>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
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