Hi I have a 6 slide experiment I'd like to be able to plot a MA plot that combines the data from all six slides and takes in to consideration duplicates on the slides I'm currently trying variations of the command as outlined on page 9 of the Limma users guide M <- fit$coef A <- apply(MA$A, 1, mean) plot(A, M etc......) However taking into consideration the duplicates. The lengths differ and the data cannot be plotted (not surprising) The spacing specified in lm.series & gls.series is 320 for my arrays so I tried to take this into consideration A <- apply(MA$A, 1, mean, spacing=320) but of course this doesn't work although it does seem to except the spacing function as a option ? the length of A is twice aslong as M apologies for my limited R knowledge..... Anyway.... any ideas how I can achieve a merged MA plot from my six slides basically I'd like to be able to plot this data and identify particular spots using identify() thanks -- -------------------------------- Jason Skelton Pathogen Microarrays Wellcome Trust Sanger Institute Hinxton Cambridge CB10 1SA Tel +44(0)1223 834244 Ext 7123 Fax +44(0)1223 494919

At 06:13 PM 7/10/2003, Jason Skelton wrote: >Hi > >I have a 6 slide experiment > >I'd like to be able to plot a MA plot that combines the data from all six >slides and takes in to consideration duplicates on the slides > >I'm currently trying variations of the command >as outlined on page 9 of the Limma users guide >M <- fit$coef >A <- apply(MA$A, 1, mean) >plot(A, M etc......) > >However taking into consideration the duplicates. >The lengths differ and the data cannot be plotted (not surprising) > >The spacing specified in lm.series & gls.series is 320 for my arrays >so I tried to take this into consideration > >A <- apply(MA$A, 1, mean, spacing=320) but of course this doesn't work >although it does seem to except the spacing function as a option ? No it doesn't. When using R, you should always look at the help page for a function to see whether it accepts a particular argument. You can't just guess. The apply() function is part of R base and doesn't know anything about microarrays. Anyway, you can do what you want using the unwrapdups() function in limma: A <- rowMeans(unwrapdups(MA$A,ndups=2,spacing=320), na.rm=TRUE) In the development version of limma, this is done automatically by the lmFit() function which stores the average A-values in the fit$Amean component. Gordon >the length of A is twice aslong as M >apologies for my limited R knowledge..... > >Anyway.... >any ideas how I can achieve a merged MA plot from my six slides > >basically I'd like to be able to plot this data and identify particular >spots using identify() > >thanks > >-- >-------------------------------- >Jason Skelton >Pathogen Microarrays >Wellcome Trust Sanger Institute >Hinxton >Cambridge >CB10 1SA > >Tel +44(0)1223 834244 Ext 7123 >Fax +44(0)1223 494919 > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor