Hi. On Tue, Oct 28, 2008 at 3:52 PM, Venkat <[EMAIL PROTECTED]> wrote: > > Thanks Henrik. > >> The QuantileNormalization class/method works for any Affymetrix chip type. >> >> There are many different ways to pre-process data out there and the >> two vignettes show to different ways. >> >> I should really put up a CRMA (v1) vignette illustrating the exact >> steps in the Bengtsson et al. (2008) paper or CRMA preprocessing (our >> preferred method) of 500K (and before), but short of time... Although >> developed for 500K (before GWS5/6 came out), the CRMA model (with some >> modifications) actually applies to GWS5/GWS6 arrays too. If replacing >> AvgCnPlm with RlmCnPlm in the GWS6 vignette, you actually have CRMA. > > As a followup is it redundant to do > > qn <- QuantileNormalization(csC) > csN <- process(qn, verbose=verbose) > > prior to > > plm <- RmaCnPlm(csN, mergeStrands=TRUE, combineAlleles=FALSE, shift= > +300) > fit(plm, verbose=verbose) > > i.e. will the plm fit from RmaCnPlm with and without the > QuantileNormalization step be the same.
No. I see your confusion: The "Rma" part of "RmaCnPlm" is referring to the RMA-style probe summarization (=the log-additive model) and not any of the other parts of the RMA model. Thus, it does not include QN. We chosed to call it Rma*Plm to show the origin of the probe-level model (PLM). LogAdditivePlm was discussed but we though it was not specific enough. We also have dChip's Mbei*Plm, and ours Affine*Plm (also a multiplicative model related to MBEI) and Avg*Plm. > > And if so does RmaCnPlm have a subsetToAvg argument. So, no, because it fit the log-additive model to each unit separately (across arrays). Hope this clarifies a few things Henrik > > Thanks, > Venkat > > > > --~--~---------~--~----~------------~-------~--~----~ When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example. You received this message because you are subscribed to the Google Groups "aroma.affymetrix" group. To post to this group, send email to aroma-affymetrix@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/aroma-affymetrix?hl=en -~----------~----~----~----~------~----~------~--~---
