OK, sorry again for the delay. We now have a function called "UPC" in
SCAN.UPC package that will produce a probability that each
is expressed above background. The parameters are identical to those
the SCAN function.
This function is part of Bioconductor 2.12, which is the current
developmental version and will be released in a few months. However,
are welcome to try it out now. You'll just need to install the
versions of R and Bioconductor. Please let me know if you have any
P.S. I've copied the Bioconductor list in case others have the same
>On 10/10/2011 Wed, Oct 10, 2011 9:59 PM, "Anthony Bosco"
><anthonyb at="" ichr.uwa.edu.au=""> wrote:
>>I have just tried your SCAN preprocessing on some microarray data
>>the results look fantastic!
>>In your paper you mention that SCAN estimates 79 % of the probes are
>>measuring noise only and have no signal above background.
>>Is it possible to flag these probes and remove them from downstream
>>From: bioconductor-bounces at r-project.org
>>[mailto:bioconductor-bounces at r-project.org] On Behalf Of W. Evan
>>Sent: Wednesday, 10 October 2012 8:27 PM
>>To: bioconductor at r-project.org
>>Cc: Andrea Bild; Steve Piccolo
>>Subject: [BioC] New Bioconductor Package: SCAN.UPC
>>Hey Bioconductor Users,
>>I just wanted to give you all a 'heads-up' on a new package
>>that appeared in last week's release of Bioconductor. In the The
>>normalization is a new single sample Affy normalization approach
>>only requires information within the sample, and does not need other
>>samples or a set of reference samples for the normalization. The
>>thing about this is that it means that once you normalize the array
>>once, the normalized values won't change if other arrays are added
>>the expression set. This has great utility in meta-analysis and in
>>personalized medicine applications.
>>The details of our SCAN method can be found here
>>SCAN removes background variation and increases the signal-to-noise
>>ratio in the samples. We are seeing instances where batch effects
>>removed or reduced from batches of data as well. The method is a
>>and uniform upgrade over RMA, and is showing slightly better or
>>equivalent results compared to fRMA. The advantage over fRMA is that
>>you don't need to provide a frozen reference vector for the
>>normalization--which is difficult for some arrays and applications.
>>Also we are seeing improved performance when combining across Affy
>>array platforms because fRMA will need different frozen vectors for
>>different array platforms.
>>Please let us know if you have any issues with the package. We are
>>happy to help!
>>Bioconductor mailing list
>>Bioconductor at r-project.org
>>Search the archives:
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