Hi Michael

               Even if i perform coloring the carcinoma it  is so crowded ,
i am not able to distinguish between cancer . That is the reason that i
wanted to find a way to point out  a single point for each cancer . My
ultimate is to find the cancer which are related , with respective my gene
of interest . Please suggest me a better approach.

thank you,
Deepak


On Wed, Jul 16, 2014 at 3:50 PM, Michael Love <michaelisaiahlove@gmail.com>
wrote:

> hi Deepak,
>
> We like to always keep the discussion on the list, to avoid having to
> answer duplicate questions.
>
> Collapsing all the patients into a single point defeats the purpose of
> PCA: to see the distances between individual samples and groups of
> samples. Showing just the mean for each group might mislead someone
> looking at the plot into thinking the clusters are distinct, when the
> samples might have high variance around that average point. I would
> recommend instead just coloring the types of carcinoma.
>
> Mike
>
> On Wed, Jul 16, 2014 at 5:43 AM, deepak karthik <deepaksrna@gmail.com>
> wrote:
> > Thanks for your reply.
> > I have data of hundreds of patients from each carcinoma , consisting of
> > rnaseq expression with certain gene of interest. If i perform pca
> analysis
> > for numerous carcinoma  , my pca plot would be clumsy difficult to find
> out
> > the type of carcinoma are clustered together . so i would like to mark
> > single point for a particular type of carcinoma with consideration of
> my
> > rnaseq expression  for my  gene of my interest . Thanks in advance .
> >
> > with regards,
> > S.Deepak
> >
> >
> > On Tue, Jul 15, 2014 at 9:31 PM, Michael Love <
> michaelisaiahlove@gmail.com>
> > wrote:
> >>
> >> You might get more feedback if you describe what kind of experiment
> >> you have performed (microarray or RNA-Seq?).
> >>
> >> The other reason you might not be getting response is that the
> >> principal component functions are not implemented in Bioconductor, but
> >> in base R. So it's not necessarily a Bioconductor question, but a
> >> statistics/R question.
> >>
> >> The very basic code for making a PCA plot from an expression set 'e'
> would
> >> be
> >>
> >> pc = prcomp( t ( exprs( e ) ) )
> >> plot( pc$x[ , 1:2 ] )
> >>
> >> On Tue, Jul 15, 2014 at 8:36 AM, karthik [guest] <
> guest@bioconductor.org>
> >> wrote:
> >> > Hi all,
> >> >
> >> >         I am writing this mail for second time. I wanted perform a pca
> >> > analysis ,for each  cancer type and genes of interest expression. I
> just
> >> > wanted to plot only a single  point which is able represent each
> cancer and
> >> > their genes expression .Can you please explain me on it.( And cancer
> per
> >> > gene basis should i take median or mean values to represent their
> >> > expression). Thanks in advance.
> >> >
> >> >
> >> >  -- output of sessionInfo():
> >> >
> >> > pca()
> >> >
> >> > --
> >> > 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
> >
> >
> >
> >
> > --
> >
> > Deepak karthik
> >
> > PhD student
> >
> > +972-054-5683140
> >
> >
> > Dr. Mali Salmon-Divon, Genomic Bioinformatics laboratory
> >
> > The Department of Molecular Biology
> >
> > Ariel University, Israel
>



-- 

*Deepak karthik*

*PhD student*

*+972-054-5683140*


*Dr. Mali Salmon-Divon, **Genomic Bioinformatics laboratory*

*The Department of Molecular Biology*

*Ariel University, Israel*

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