you should keep the correspondence on the mailing list so that others can
learn.  do you have raw intensity data?  if so then if you want to follow
the instructions that you have excerpted try to take log but watch out for
zeroes or negative numbers in case background correction was performed.  if
the data are already logged then skip that step.  the best thing would be
for you to talk to a statistician in your organization -- there is nothing
in this problem that you are posing that is specific to microarrays.  you
are asking about aspects of data analysis that are encountered in every
field and the most reliable solutions depend upon context and facts about
the data.

On Thu, Sep 16, 2010 at 8:02 PM, zhliu.tju <zhliu.tju@gmail.com> wrote:

> Thanks a lot for response, I am new to microarray so I am not sure of some
> definition and process of microarray data analysis.
> The problem is that although I read those materials about microarray,
> hardly could I confirm or understand fully the definition. Some description
> lack some basic information which is common sense for veteran but too
> difficult for novice.
>
> Now I found a paragraph which I am not sure about the exact meaning, thus I
> wonder if I could confirm with you.
>
> "Given a particular subnetwork M, let *a* represent its vector of activity
> scores over the tumor samples, and let *c* represent the corresponding
> vector of class labels (metastatic or non-metastatic). To derive *a*,
> expression values *g**ij* are normalized to z-transformed scores *z**ij*which for each gene
> *i* has mean [image: mu]=0 and s.d. [image: sigma]=1 over all samples *j*(Box
> 1 <http://www.nature.com/msb/journal/v3/n1/box/msb4100180_BX1.html>)."
>
> I also searched some materials about z-score transformation in
> http://jmd.amjpathol.org/cgi/content/full/5/2/73.
>
> *"Z Score Transformation*
> Raw intensity data for each experiment is log10 transformed and then used
> for the calculation of *Z* scores. *Z* scores are calculated by
> subtracting the overall average gene intensity (within a single
> experiment) from the raw intensity data for each gene, and dividing that
> result by the SD of all of the measured intensities, according to the
> formula:
>  where G is any gene on the microarray and G1... Gn represent the
> aggregate measure of all of the genes."
>
> I want to do gene wise z score transformation, so I wonder if I should
> firstly log transform raw data and then calculate gene wise z score which
> for each gene calculate z score over different assays.
>
> Anyway, thanks a lot!
>
> Zhe
>
> On 8 September 2010 00:33, Vincent Carey <stvjc@channing.harvard.edu>wrote:
>
>> Your questions are a little too broad to be answered comfortably,
>> likely the reason
>> for lack of response.  Comments below; please read the posting guide
>> before posting more.
>>
>> On Sun, Sep 5, 2010 at 3:22 PM, zhliu.tju <zhliu.tju@gmail.com> wrote:
>> > Dear all,
>> >
>> > I am a rookie in microarray data analysis and I not familiar with
>> illumina
>> > software and the result format of beadstudio software. Now I got
>> microarray
>> > data, but I am not sure about the process they have done to these data.
>> >
>> > 1. Normalized data means they are preprocessed and normalized, if they
>> are
>> > log transformed?
>>
>> You are asking for a definition of "normalized"?  In general it means
>> there has been
>> an attempt to remove biologically unimportant sources of variation.
>> The bead studio documentation
>> should be consulted for details on what it can do, and the lab techs
>> should be queried
>> concerning what was actually done.
>>
>> > 2. If I want to zscore transform the normalized data, if I should do log
>> > transformation first?
>>
>>
>> > 3. In addition, illumina microarray data is one channel data, but I
>> donot
>> > know what is the difference between one channel data and two channel
>> data?
>>
>> You cannot reasonably expect readers of the the mailing list to
>> address this issue.  You have to do some reading
>> about general concepts of microarray analysis.  The table of contents
>> in the wikipedia article
>> http://en.wikipedia.org/wiki/Dna_microarray addresses the topic of one
>> vs two channels directly, and many other texts
>> can be found to introduce the concepts.
>>
>> >
>> > Thanks a lot!
>> >
>> > Zhe
>> >
>> >        [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > Bioconductor mailing list
>> > Bioconductor@stat.math.ethz.ch
>> > https://stat.ethz.ch/mailman/listinfo/bioconductor
>> > Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>> >
>>
>
>

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