Sorry! It wasn't my intention...

Thank you for your help,

Avhena

On Wed, Feb 17, 2010 at 11:42 AM, James W. MacDonald
<jmacdon@med.umich.edu>wrote:

> Hi Avehna,
>
> Please don't take conversations off list. The list is considered to be a
> resource that people in your situation can use in the future to answer
> questions themselves.
>
> avehna wrote:
>
>  On Tue, Feb 16, 2010 at 3:50 PM, James W. MacDonald <
>> jmacdon@med.umich.edu <mailto:jmacdon@med.umich.edu>> wrote:
>>
>>    To add to this; these data are almost surely MAS5 processed data, as
>>    I don't know of any other algorithm that gives the detection
>>    p-value. In addition, the range of 0 - 9000 indicates that these
>>    data are not logged (which is the next step for you). People
>>    normally use log base 2 so that a difference of 1 or -1 indicates
>>    two-fold up or down regulation.
>>
>>
>> OK. But in this case what would be the reference point? Wouldn't be the up
>> or down regulation respect to the control? Before writing to the list I have
>> browsed several tutorials and I'm still missing this part. Should it be
>> log2(treatment/control)? (It's not clear what I have read)
>>
>
> Yes. Or since you have already taken logs, it will be log2(treatment) -
> log2(control), which you will notice is the numerator of your t-statistic.
>
>
>
>
>>
>>    MAS5 data are normalized after the fact, so you should log transform
>>    and then look at plots of the densities to see if they look as if
>>    they have been normalized or not. The default is to do a scale
>>    normalization, so you are just looking for the densities to be in
>>    same general vicinity rather than overlaying each other.
>>
>>
>> OK. Could you send me some helpful references about that?
>>
>
>
> http://media.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf
>
> Best,
>
> Jim
>
>
>
>>
>>    If you could get the original celfiles, you would be much better off.
>>
>>
>> I will try!
>>
>> Best and thank you so much for your help,
>>
>> Avhena.
>>
>>    Best,
>>
>>    Jim
>>
>>
>>
>>
>>    michael watson (IAH-C) wrote:
>>
>>        This is definitely processed data, and without access to the
>>        original data or a description of the analysis methodology, your
>>        options are limited.
>>
>>        Personally, I'd do a test for normality on the "Signal" values,
>>        and if they turn out to be normal, I'd run a simple t-test
>>        (control vs treatment) on each gene and correct the p-values for
>>        multiple testing.
>>
>>        Simple stuff, but it should work.
>>        ________________________________________
>>        From: bioconductor-bounces@stat.math.ethz.ch
>>        <mailto:bioconductor-bounces@stat.math.ethz.ch>
>>
>>        [bioconductor-bounces@stat.math.ethz.ch
>>        <mailto:bioconductor-bounces@stat.math.ethz.ch>] On Behalf Of
>>        avehna [avhena@gmail.com <mailto:avhena@gmail.com>]
>>
>>        Sent: 16 February 2010 19:47
>>        To: bioconductor@stat.math.ethz.ch
>>        <mailto:bioconductor@stat.math.ethz.ch>
>>
>>        Subject: [BioC] DNA micro-array normalization
>>
>>        Hi There,
>>
>>        I've got a DNA microarray dataset that looks like this:
>>
>>        *    Probe                 Signal          Detection
>>        Detection_p-value                   Descriptions*
>>        AFFX-BioB-5_at       181                P
>>        0.00011                  "E. coli  GEN=bioB  DB_XREF=gb:J04423.1"
>>        AFFX-BioB-M_at     227.3              P                 0.000044
>>          "E. coli  GEN=bioB  DB_XREF=gb:J04423.1"
>>        AFFX-BioC-5_at     499.2               P
>>        0.000052                "E. coli  GEN=bioC  DB_XREF=gb:J04423.1"
>>
>>        I have control and treatment with 3 replicas for each one of them.
>>
>>        But I'm not sure whether these data have been already
>>        normalized, and on the
>>        other hand, this is not the typical affymetrix format...
>>
>>        Could you help me in this regard? What is the typical signal
>>        range for rough
>>        affymetrix data? (these data range from 0 to 9000)
>>
>>        If the data have been already normalized, Can I calculate the
>>        mean (for
>>        treatment and control) followed by the differential expression
>>        of genes
>>        without taking into account the "Detection" column?
>>
>>        (I guess I will need to build my ExpressionSet from scratch)
>>
>>        Thanks a lot (I'm a newbie in bioconductor and micro-array
>>        analysis). I will
>>        appreciate you help!
>>
>>        Avhena
>>
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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.
>>    Ann Arbor MI 48109-5618
>>    734-615-7826
>>    **********************************************************
>>    Electronic Mail is not secure, may not be read every day, and should
>>    not be used for urgent or sensitive issues
>>
>>
>>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
> Ann Arbor MI 48109-5618
> 734-615-7826
> **********************************************************
> Electronic Mail is not secure, may not be read every day, and should not be
> used for urgent or sensitive issues
>

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