[BioC] Suggestions on Agilent gene expression data
Sean Davis
sdavis2 at mail.nih.gov
Thu Jun 12 12:29:23 CEST 2008
On Wed, Jun 11, 2008 at 10:15 PM, ss <affysnp at gmail.com> wrote:
> Hi Sean,
>
> Thanks a lot! The data we downloaded has already been normalized and
> processed.
> So I guess I can go ahead without further quality control.
I would not make the assumption that all is well with the data without
looking at some plots, etc., but I suppose that it depends on what you
are doing with the data and how much you care about the results.
> My question then
> is that
> if I want to utilize some other tools or softwares for higher level
> analysis, should I use
> ratio, or log2(ratio) or Log(ratio)? Or it does not matter at all?
> On Wed, Jun 11, 2008 at 10:01 PM, Sean Davis <sdavis2 at mail.nih.gov> wrote:
>
>> On Wed, Jun 11, 2008 at 7:43 PM, ss <affysnp at gmail.com> wrote:
>> > Dear all,
>> >
>> > For whom is familiar with Agilent gene expression data, I would like to
>> > ask help.
>> >
>> > We recently received some Agilent gene expression data from our
>> > collaborators. For individual sample, there are 7 corresponding columns:
>> >
>> > Unknown:Log(Ratio) Unknown:Ratio Unknown:Fold Change
>> Unknown:Log(Error)
>> > Unknown:P-Value Unknown:Intensity 1 Unknown:Intensity 2
>> > It seems that Ratio= Intensity1/Intensity2. I wonder whether I should use
>> > log2(Ratio) or Log(Ratio) or just Ratio for further analysis. Besides,
>> why
>> > should Ratio be calculated as Intensity1/Intensity2 instead of
>> > Intensity2/Intensity1?
>>
>> Hi, Allen. You'll probably need to do some quality control and some
>> normalization. The choice of ratio is arbitrary; you can always
>> invert it if it is more convenient to do so. As for log2 or log, they
>> are equivalent to each other with the exception of a constant. You
>> might look at the limma manual for some guidance on working with
>> two-color arrays.
>>
>> Sean
>>
>
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>
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