Dear Sean,

Thank you for your reply. At this time, I am left with no choice but to
deal with the data as-is. I realize that it is hard to work without
replicates, but is there any way to make maximum meaningful info from this
limited data set that I have? Some other tools/algorithms/packages/tests?

Also, what does the contents of ProcessedData.txt file exported from
AgiMicroRna mean? As far as I know, they are the Total Gene Signals of all
those miRNAs that pass the filtering step. Isn't it? So, what downstream
tests can I do using it as an input file? As mentioned in my previous post,
I am interested in finding out the differentially expressed genes between
my control and treated samples.


Thanks a lot again.

Karthik

On Mon, Feb 6, 2012 at 7:21 PM, Sean Davis <sdavis2@mail.nih.gov> wrote:

> On Mon, Feb 6, 2012 at 8:29 AM, Karthik K N <karthikuttan@gmail.com>
> wrote:
> > Dear Lucas,
> >
> > I am using AgiMicroRna package and came across the same error that you
> also
> > had i.e., Error in ebayes: No residual degrees of freedom in linear model
> > fits.
> >
> > I read your posts<
> https://stat.ethz.ch/pipermail/bioconductor/2009-May/027834.html>and
> > the replies to that.
> >
> > My dataset consists of just 2 different arrays, one control and one
> > treated. I am trying to find out diferentially expressed genes between
> > them.
> >
> > >From the reply to your post I understood the reason why I am seeing this
> > error with eBayes. I just wanted to ask help from you on how will I be
> able
> > to find out differentially expressed genes between these datasets?
> >
> > I saw you mentioning BGX, but will that work with Agilent miRNA
> microarray
> > platform? My idea is that it will not.
> >
> > If there is there anything that you can do to help me solve this, I will
> be
> > really thankful to you.
>
> Hi, Karthik.
>
> The "No residual degrees of freedom" in your case is statistical
> language meaning that you do not have enough samples to perform the
> number of tests you want to perform.  In your case, this is a problem
> because it is not possible to do a statistical hypothesis test with
> only two samples.  This is not a software problem but a statistical
> issue.  To "fix" the problem, you will need to perform some biologic
> replicates.
>
> To deal with your data as-is, you can simply compute a ratio between
> treatment and control.
>
> Sean
>



-- 
Karthik K.N

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