there was a package addressing cross-sample distributional shapes, edd, but it was retired due to lack of use, IIRC
http://books.google.com/books?id=jIMO2rRaCbMC&pg=PA55&lpg=PA55&dq=edd+expression+density+diagnostics&source=bl&ots=tXKdRicJ8x&sig=vZF9tRCrLAhiaVinx7yeEMh3bSA&hl=en&sa=X&ei=DgOyUbitItLl4AOXhYHYAQ&ved=0CFAQ6AEwBw#v=onepage&q=edd%20expression%20density%20diagnostics&f=false On Fri, Jun 7, 2013 at 11:26 AM, James W. MacDonald <jmac...@uw.edu> wrote: > Hi Miguel, > > > On 6/7/2013 5:11 AM, Miguel Moreno-Risueno wrote: > >> >> >> Hello all, >> >> >> >> We have recently received a microarray experiment in the Nimblegen >> platform >> where the intensity of the probe sets follow a bi-modal distribution. We >> have been said from the facility that this is because of the dynamic range >> of the Agilent scanner they use. We are concerned about the statistical >> analysis with bioconductor as it is our understanding that these >> statistical >> analyses are developed for normal or normal-like distribution. We >> appreciate >> any information on this regard. >> > > If I understand your question correctly, you are noting that the overall > distribution of probes within a sample has a bi-modal distribution. This > doesn't really have anything to do with any statistical tests you might be > computing, as you are not doing any statistics within a sample (e.g., one > usually doesn't test to see if probe X is differentially expressed as > compared to probe Z in sample Q). > > Instead, what you should be concerned with are the distributions of the > individual probes across samples. With microarray data we usually don't > have enough data to even begin to assess the across-sample, within probe > distributions (e.g., if you have three replicates for two sample types, > good luck trying to discern if those probes follow a normal distribution, > or are even 'hump-shaped'). In addition, there are usually tens of > thousands of probes on a given chip. I have never heard of anybody looking > at each probe, trying to assess if it follows a reasonable distribution > across samples. I suppose you could do it, but to what point? > > Instead we simply assume that the data follow a reasonable distribution > and then do the test. This is one of the reasons that it is imperative to > follow up promising leads with confirmatory testing, preferably with new > samples. > > Best, > > Jim > > > > >> >> >> Thank you in advance for your help, >> >> >> >> Miguel >> >> >> >> >> >> >> [[alternative HTML version deleted]] >> >> ______________________________**_________________ >> Bioc-devel@r-project.org mailing list >> https://stat.ethz.ch/mailman/**listinfo/bioc-devel<https://stat.ethz.ch/mailman/listinfo/bioc-devel> >> > > -- > James W. MacDonald, M.S. > Biostatistician > University of Washington > Environmental and Occupational Health Sciences > 4225 Roosevelt Way NE, # 100 > Seattle WA 98105-6099 > > > ______________________________**_________________ > Bioc-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/**listinfo/bioc-devel<https://stat.ethz.ch/mailman/listinfo/bioc-devel> > [[alternative HTML version deleted]] _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
