[BioC] RMA normalization,which samples should be normalized together

[Naomi Altman]

Note: I should have said "paired t-test" and "paired Wilcoxon test" in my 
comments below.

--Naomi

At 10:44 AM 2/7/2005, Naomi Altman wrote:
>Dear Johannes,
>Actually, technical replication is of little interest when you have 
>biological replication.  If I understand your experiment, you have 40 
>patients, each measured at 2 times.
>
>Because of the pairing, you have several options for appropriate 
>normalization and analysis:
>
>1) Normalize the before and after for each patient together, and analyze M.
>
>You could use either RMA, or a simpler M vs A loess for this.
>
>2) Normalize all the arrays together and then compute M for each patient.
>
>I would use RMA or gcRMA for this.
>
>In either case, I would simply use limma with the 
>contrast   rep(1,npatients) since this gives the t-test for before-after 
>which seems to be of most interest.  Limma has an advantage over ordinary 
>t-tests in that it combines some information across genes.  However, I 
>expect it to be very similar to ordinary t-tests (or Wilcoxon tests) 
>because you have a fairly large sample size.  Any of these methods are 
>appropriate.
>
>Incidentally, the technical reps are interesting for quality control, but 
>should not be included in this analysis.
>
>--Naomi
>
>At 09:48 AM 2/7/2005, Dipl.-Ing. Johannes Rainer wrote:
>>thanks arne
>>
>>i have no replicates, affymetrix is still a little bit expensive ;) . all 
>>our chips were made by ourself and by looking at the histograms of the 
>>raw values there are no differences at all. in the whole experiment we 
>>made also two replicates, one with the same RNA, but different amount 
>>before amplification (one time 5 mug, the second time 1 mug) and the 
>>second replicate is RNA from the same patient, same time point, but the 
>>RNA was extracted by two different people  not at the same time. if i 
>>normalize only those replicated chips i see nearly no differences between 
>>them (with a M (log2 regulation value) cut off of M=1 i get about 30 
>>probe sets that differ), but when i normalize all 80 chips of all 
>>patients together the replicated chips show more differences... in my 
>>opinion i have to normalize all patient chips together, exspecially if i 
>>want to do for example a wilcox between all 0 hour and 6 hours chips.
>>can you tell me a little bit more about the linear model you have used to 
>>merge the results?
>>
>>regards, jo
>>
>>
>>Quoting Arne.Muller at sanofi-aventis.com:
>>
>>>Dear Johannes,
>>>
>>>I've a study with 84 affy chip to characterize a dose effect of a drug. 
>>>The study was conducted in 3 different laboratories. There are strong 
>>>differences betweent the laboratories and I've RMA normalized per 
>>>laboratory and then merged the results in a single linear moel including 
>>>the laboratory as an additional factor. Maybe you can make the patient 
>>>or source of RNA a random factor in a mixe effects model - if you've 
>>>replication per patient.
>>>
>>>Just looking at those genes with a significant dose effect I did not 
>>>find much differences between normalizing all chips together and
>>>normalizing per laboratory.
>>>
>>>         regards,
>>>
>>>         Arne
>>>
>>>
>>>>-----Original Message-----
>>>>From: bioconductor-bounces at stat.math.ethz.ch
>>>>[mailto:bioconductor-bounces at stat.math.ethz.ch]On Behalf Of Dipl.-Ing.
>>>>Johannes Rainer
>>>>Sent: 07 February 2005 10:13
>>>>To: bioconductor at stat.math.ethz.ch
>>>>Subject: [BioC] RMA normalization,which samples should be normalized
>>>>together
>>>>
>>>>
>>>>hi,
>>>>we are interested in the response of patients to a special treatment,
>>>>so we have patient samples before and after treatment. i have
>>>>normalized this samples in different ways using RMA. As RMA tries to
>>>>detect and correct probe effects by looking at the expresison
>>>>levels of
>>>>the probes across all chips it is not surprising that the outcome of
>>>>the analysis differs depending on which chips i normalize together.
>>>>It is clear that i have to normalize all patient samples
>>>>together if i
>>>>want to compare the expression values of the genes (lets say using
>>>>statistical tests). i am also analyzing the chips using the 'old
>>>>fashioned way' by using M and A values and i suppose it is not
>>>>problematic at all to compare M values of lets say patient 1, 6 hours
>>>>sample against 0 hours sample with those from patient 2, also 6 hours
>>>>versus 0 hours where the chips from the two patients were NOT
>>>>normalized together.
>>>>
>>>>-now my question is if someone else has experience in what samples
>>>>could and should be normalized together with RMA. I saw that ther are
>>>>(big) differences in the regulation (M) values if i normalize two
>>>>different patients together compared with the values that i
>>>>get when i
>>>>normalize only samples from the same patients together.
>>>>
>>>>thanks in advance
>>>>
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>>
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>
>Naomi S. Altman                                814-865-3791 (voice)
>Associate Professor
>Bioinformatics Consulting Center
>Dept. of Statistics                              814-863-7114 (fax)
>Penn State University                         814-865-1348 (Statistics)
>University Park, PA 16802-2111
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111