Dear Sir,
Thank you for your valuable suggestion. Will definitely look into it.

I've one more question though.
Sir, if we have only two datasets (say lung and liver), we can calculate
log ratio (lung/liver) and finally fold change (2^log_ratio , considering
log2 ratio).
But in this case, if i want to determine the differentially expressed genes
based on Fold Change, how do i that??
Do i have to take the ratio of expression value of each tissue with all
other remaining tissues??

Sorry again, if my question doesn't make any sense.


On Wed, Nov 23, 2011 at 5:43 PM, Sean Davis <sdavis2@mail.nih.gov> wrote:

> Hi, Anand.
>
> Please try to keep the conversations on the list so that you can get
> the best answers to your questions.
>
> First, you will need to split the data back out to include the values
> for all your replicates.  In other words, do not use the means.
> Working with means only essentially precludes any statistical testing
> at all.
>
> Second, I would suggest that you take a look at the limma package and
> the wonderful limma user guide.  The statistical framework used in
> limma is the linear model and it works well for two-class or
> multi-class problems.
>
> Sean
>
>
> On Wed, Nov 23, 2011 at 6:40 AM, anand m t <anandrox05@gmail.com> wrote:
> > Sir,
> > I'm tying to compare the data from all the brain tissues. The data which
> > i've shown here is the mean value of all 3 biological replicates of each
> > tissue.
> >
> > On Wed, Nov 23, 2011 at 4:57 PM, Sean Davis <sdavis2@mail.nih.gov>
> wrote:
> >>
> >> On Wed, Nov 23, 2011 at 5:14 AM, anand mt [guest]
> >> <guest@bioconductor.org> wrote:
> >> >
> >> > hi all,
> >> >
> >> > i'm new to this microarray data  analysis.
> >> > recently i've been given data consisting of 11 tissues.
> >> > now i've normalized the data, filtered data using mas5 AP calls. My
> >> > question is, which statistical test i must perform
> >> > to calculate the significance values ??
> >> >
> >> > sample data is as below:
> >> >
> >> >
> >> >        accumbens       amygdala        cerebellum      corpus.collosum
> >> > hippocampus     midbrain        p.lobe  putamen s.nigra t.lobe
>  thalamus
> >> > 1007_s_at       11.93852233     12.21404093     11.46118612
> >> > 13.41594885     12.42216256     12.89589133     11.58715914
> 11.85803472
> >> >     12.79920479     12.07087932     12.55338306
> >> > 1053_at 7.490706858     7.526181155     7.551069308     7.891002293
> >> > 7.49104271      7.971097552     8.088918072        7.660258014
> >> > 7.92423132      7.54689645      7.128753703
> >> > 117_at  8.486898268        8.773089087        7.642339349
> >> > 8.560352732     7.676296801     7.865961146        7.250275943
> >> > 7.929165261     7.874073766        7.940298941     8.10731601
> >> >
> >> >
> >> > I got some web results, from which i came to know that, chi-square
> test
> >> > is of more relevant in this case (to compare 3 or more unmatched
> groups,
> >> > binomial). Is it correct to choose chi-square test ??
> >> >
> >> > Sorry if my question is too lame.
> >>
> >> Hi, Anand.
> >>
> >> I'm assuming that for you the biological question that you are asking
> >> is obvious, but to me it seems unclear.  In particular, what groups
> >> above are you trying to compare?  It seems you have no replicates?
> >>
> >> Sean
> >>
> >>
> >> > thanks in advance.
> >> >
> >> >  -- output of sessionInfo():
> >> >
> >> > R version 2.13.1 (2011-07-08)
> >> > Platform: i386-pc-mingw32/i386 (32-bit)
> >> >
> >> > locale:
> >> > [1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United
> >> > States.1252    LC_MONETARY=English_United States.1252 LC_NUMERIC=C
> >> > [5] LC_TIME=English_United States.1252
> >> >
> >> > attached base packages:
> >> > [1] stats     graphics  grDevices utils     datasets  methods   base
> >> >
> >> > other attached packages:
> >> > [1] MASS_7.3-13
> >> >
> >> > loaded via a namespace (and not attached):
> >> > [1] tools_2.13.1
> >> >
> >> > --
> >> > Sent via the guest posting facility at bioconductor.org.
> >> >
> >> > _______________________________________________
> >> > Bioconductor mailing list
> >> > Bioconductor@r-project.org
> >> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> >> > Search the archives:
> >> > http://news.gmane.org/gmane.science.biology.informatics.conductor
> >> >
> >
> >
> >
> > --
> > ******************************************************************
> > Anand M.T
> > School of Biotechnology (Bio-Informatics),
> > International Instituteof Information Technology (I2IT),
> > P-14, Rajiv Gandhi Infotech park,
> > Hinjewadi,
> > Pune-411 057.
> > INDIA.
> >
>



-- 
******************************************************************
Anand M.T
School of Biotechnology (Bio-Informatics),
International Instituteof Information Technology (I2IT),
P-14, Rajiv Gandhi Infotech park,
Hinjewadi,
Pune-411 057.
INDIA.

"The secret of success comprised in three words.. Work, Finish & Publish" -
Michael Faraday

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