SCAN-UPC-R download link appears to be broken:

http://jlab.bu.edu/files/2012/08/SCAN-UPC-R.tar.gz

thanks!

--t


On Thu, Sep 6, 2012 at 5:22 AM, W. Evan Johnson <wej@bu.edu> wrote:

> Santana,
>
> The first thing I always do is hierarchical clustering. Often, batch
> effects are easily spotted with this simple approach. Then try something
> like PCA.
>
> Also, just to point out, we have recently published a single-sample
> normalization approach, SCAN, that does a better job at normalizing the
> arrays. Often, artifacts that look like 'batch effects' drop out in the
> normalization step with this approach. We've shown in several cases that
> this approach does a better job at combining data than anything else out
> there, so it will give you a cleaner starting point. After SCAN
> normalization, if you still have batch effects, try ComBat or sva (both in
> the sva package). This will likely be all you need for your batch effects.
>
> Here is a link to our SCAN paper:
> http://www.sciencedirect.com/science/article/pii/S0888754312001632
> Here is a link to our SCAN software: http://jlab.bu.edu/software/scan-upc/
>
> SCAN is available in both R and Python at the site.
>
> Hope this helps!
>
> Evan
>
>
> On Sep 6, 2012, at 6:00 AM, bioconductor-request@r-project.org wrote:
>
> > Message: 19
> > Date: Wed, 5 Sep 2012 20:46:58 -0400
> > From: Jeff Leek <jtleek@gmail.com>
> > To: Wolfgang Huber <whuber@embl.de>
> > Cc: bioconductor@r-project.org
> > Subject: Re: [BioC] Batch effect
> > Message-ID:
> >       <
> CAGWgrqNPDHCFwVH2nhf8ZXnfBk_KDy_DMEER_5NMSDxsjbXTxQ@mail.gmail.com>
> > Content-Type: text/plain
> >
> > Hi Santana,
> >
> > You might also try the sva function in the sva package. This function is
> > specifically designed to identify batch effects and other sources of
> > variation. PCA typically confounds any signal of interest with potential
> > batch effects, so may be somewhat deceiving, particularly if the batches
> > are not balanced across groups of interest.
> >
> > Best,
> >
> > Jeff
> >
> > On Wed, Sep 5, 2012 at 5:35 PM, Wolfgang Huber <whuber@embl.de> wrote:
> >
> >> Dear Santana
> >>
> >> you could try the arrayQualityMetrics function in the eponymous package,
> >> which produces PCA plots and other diagnostics and is helpful to detect
> >> batch effects.
> >>
> >> The function runs either on the AffyBatch object, or the normalised
> >> ExpressionSet; the former is more useful to understand how well the
> >> experiment worked, the latter, how well subsequent analyses might work.
> >>
> >>        Best wishes
> >>        Wolfgang
> >>
> >>
> >> Sep/5/12 3:10 PM, James W. MacDonald scripsit:
> >>
> >> Hi Santana,
> >>>
> >>> On 9/5/2012 2:14 AM, Santana Sarma wrote:
> >>>
> >>>> Hi,
> >>>>
> >>>>
> >>>> How is it possible to judge whether there is any batch effect in two
> >>>> groups
> >>>> of Affymetrix .cel files ? I have got currently one Affybatch object
> by
> >>>> reading all the .cell files.
> >>>>
> >>>
> >>> There are several things you can look at. I find PCA plots very helpful
> >>> to look for batch effects. You might also look at density plots (hist()
> >>> function in affy) as well as boxplots. But IMO PCA is the most useful.
> >>>
> >>> Best,
> >>>
> >>> Jim
> >>>
> >>>
> >>>
> >>>>
> >>>> Being new to Affymetrix analysis, any advice/elaboration will be very
> >>>> helpful.
> >>>>
> >>>>
> >>>> Cheers,
> >>>>
> >>>> Santana
> >>>>
> >>>>    [[alternative HTML version deleted]]
> >>>>
> >>>> ______________________________**_________________
> >>>> Bioconductor mailing list
> >>>> Bioconductor@r-project.org
> >>>> https://stat.ethz.ch/mailman/**listinfo/bioconductor<
> https://stat.ethz.ch/mailman/listinfo/bioconductor>
> >>>> Search the archives:
> >>>> http://news.gmane.org/gmane.**science.biology.informatics.**conductor
> <http://news.gmane.org/gmane.science.biology.informatics.conductor>
> >>>>
> >>>
> >>>
> >>
> >> --
> >> Best wishes
> >>        Wolfgang
> >>
> >> Wolfgang Huber
> >> EMBL
> >> http://www.embl.de/research/**units/genome_biology/huber<
> http://www.embl.de/research/units/genome_biology/huber>
> >>
> >>
> >> ______________________________**_________________
> >> Bioconductor mailing list
> >> Bioconductor@r-project.org
> >> https://stat.ethz.ch/mailman/**listinfo/bioconductor<
> https://stat.ethz.ch/mailman/listinfo/bioconductor>
> >> Search the archives: http://news.gmane.org/gmane.**
> >> science.biology.informatics.**conductor<
> http://news.gmane.org/gmane.science.biology.informatics.conductor>
> >>
> >
> >       [[alternative HTML version deleted]]
>
> _______________________________________________
> 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
>



-- 
*A model is a lie that helps you see the truth.*
*
*
Howard Skipper<http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf>

	[[alternative HTML version deleted]]

