Forget to CC to the list (and could be relevant to others) L. 03/05/2002 14:55:35, Laurent Gautier <laurent@genome.cbs.dtu.dk> a ?crit: >On Fri, May 03, 2002 at 03:22:16PM +0200, julien.sylvestre@wotan.ens.fr wrote: >> * I've been using the affy package for a few days, and found it very well made, and really useful. By the way, thanks to all of yours for building a well documented and coherent software collection, which >> remains somewhat rare in the microarray domain, everyone tending to write it's own little program... >> >> * Yesterday, after switching to the 1.0 version (on Win2K / R1.5.0) , I experienced the following problem while fitting the Li & Wong Model : >> // liw2 = express(pl1, normalize = F, summary.stat = li.wong) >> // Background correcting >> // Preparing Data >> // Computing expression. This may take a while. >> // Error in data.matrix[, !phi.outliers] %*% phi[!phi.outliers] : >> // non-conformable arguments > > > >In does not seem the code used/called by 'express' was modified recently. Could you specify with >which version it was working ? > >What gives 'traceback()' ? (type that right after you had the error) > >> >> What does this error mean ? > >that we have an... <embarassed cough="">... undocumented feature... ;-) > > >> I had no problem when applying the default summary.stat with affy 1.0 and the same plobe level object. >> I had no problem either with the former version, the same plob and Li.Wong . >> > >Do you get the same when going through the Cel.container mecanism ? > > > > > >> Thank you in advance. >> >> JS, >> >> * PS. One minor thing maybe somebody can help me with : >> I have 12 yeast chips to analyse and the experimental design is quite well suited for ANOVA (1 factor A with 2 levels, 1 factor B with 3 levels, 2 reps C for each). >> I tried 'lm' and 'aov' on R but encountered serious memory problems despite setting memory.limit(size = 4000) and having 1GoRam plus a lot of free hard drive. >> I tried 'anovan' from Matlab Stat Toolbox, which of course resulted in a complete failure. >> In fact I'm not necesserally interested in fitting a whole model, with thousands of gene effects, but just in calculating the average A, B , C , A*B , A*C , B*C effects. I know it can be done with proc anova on >> SAS but if it were possible, would prefer to do the whole thing under R. Does anyone know any package or function I could use ? >> > >?! >Could you give us more details about the way you proceed ? >(note: the code of the function 'Anova' in the package 'genefilter' could be helpful) > > > > >Cheers, > > > >Laurent > > > > >-------------------------------------------------------------- >Laurent Gautier CBS, Building 208, DTU >PhD. Student D-2800 Lyngby,Denmark >tel: +45 45 25 24 85 http://www.cbs.dtu.dk/laurent > ************** * Je n'ai pas essay? le 'Cel.container mecanism' ; ce qui me para?t ?trange c'est que cel? fonctionnait avant (version 0.8) et que ?a fonctionne avec d'autres m?thodes. Pour information, j'obtiens ?a en tapant 'traceback()': 6: fit.li.wong(t(data.matrix), remove.outliers, normal.array.quantile, normal.resid.quantile, large.threshold, large.variation, outlier.fraction, delta, maxit, outer.maxit, verbose) 5: FUN(X[[3]], ...) 4: lapply(as.list(X), FUN, ...) 3: sapply(data.lst, summary.stat, ...) 2: t(sapply(data.lst, summary.stat, ...)) 1: express(pl1, normalize = F, summary.stat = li.wong) * Je vais regarder genefilter, en fait je pensais que c'?tait tr?s orient? puces cDNA . Effectivement, l'id?al serait davoir une ANOVA g?ne par g?ne.