similar to: background normalization in rma() in the affy package

Dear all, I was trying to normalize a subset of affy data those transcribe are either P or M (called pm_filter). I am able to normalize pm_filter subset by using RMA method, however MAS5 is not working. For RMA method, I used the following commend: est<-rma(affydata, subset=pm_filter). Could any help me; how do I do this by using MAS5 method? Regards, Anup Som -- Dr. Anup Som,

I run R 1.9.0 on windows 2000, and have the following libraries installed: affydata_1.3.1 affy_1.4.23 Biobase_1.4.10 DynDoc_1.3.14 gcrma_1.0.6 hgu133acdf_1.4.3 hgu95av2cdf_1.4.3 hgu95av2probe_1.0 matchprobes_1.0.7 moe430acdf_1.4.3 multcomp_0.4-6 mvtnorm_0.6-6 rae230acdf_1.4.3 reposTools_1.3.29 rgu34acdf_1.4.3 tkWidgets_1.5.1 widgetTools_1.2.7 1. The rma function (in affy library) always crashes.

Can anybody explain why RMA has to have a default normalization method: quantile-quantile? Why don't leave the choices to users? If I just want to use RMA to do a background correction without normalization, how should I specify the ? in the normalize.method="?" ? Hairong [[alternative HTML version deleted]]

Dear R Users, In the expresso function, which combination of these methods for data pre-processing (when using affymetrix oligo arrays) is the best: bgcorrect.metod = rma rma2 mas normalize.method = qspline quantiles loess pmcorrect.method = pmonly subtractmm mas summary.method = liwong avgdiff medianpolish mas There are many options within each method. I would appreciate a hint on the best

Hello All, I need your help. I am analysing affymetrix data and have to select the probe-set that has median expression among all the probe-sets for same gene. This way I want to remove the redundancy by keeping the analysis to single gene entry level. I am fully aware that it is not a nice thing to do but I just have to do it. To do so, I came across 'findLargest' function of

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many

Hi (R 2.13.1, OSX 10.6.8) I am trying to use predict.rma with continuous and categorical variables. The argument newmods in predict.rma seems to handle coviariates, but appears to falter on factors. While I realise that the coefficients for factors provide the answers, the goal is to eventually use predict.rma with ANCOVA type model with an interaction. Here is a self contained example

I think that you misunderstood me. As far as I know, RMA does three things: background correction, quantile normalization, and summary from probes to probesets. I want the probe values after background correction and quantile normalization but before the summary. On Sat, Dec 26, 2009 at 12:07 PM, Benilton Carvalho <bcarvalh at jhsph.edu> wrote: > pm(data) > > b > > On Dec

Hi *, is there a way to obtain some kind of p-value for a model fitted with RMA using the lmodel2 package? I know that p-values are discussed and criticized a lot and as you can image from my question I'm not very much of a statistican (only writing my bachelor thesis). As fare as I understood the confidence interval statistic correctly, a coefficient is regarded as statistically significant

Dear R-experts! I am working on some meta-analysis using the metafor package. I would like to extract values of the confidence intervals of the effect sizes of the single studies from an rma object. Those values are printed out when plotting a forest plot using the forest function on the rma object, however I was not able to locate them. Many thanks for your help! Jokel [[alternative HTML

Dear R community, I'm using the ,metafor'-package by Wolfgang Viechtbauer (Version: 0.5-5) to calculate random-effects meta-analyses using Correlations and Sample Sizes as the raw data. (By the way: Really a nice piece of work, Wolfgang! Thanks heaps.) I specified the "rma.uni' function so that it looks like this: MAergebnis<-rma.uni(ri=PosOutc, ni=N,

Hi, I'm regressing various body dimensions upon body mass using the 'lmodel2' function, as I'm keen to obtain both OLS and RMA slope values. I also wish to create a plot of the regressions, with the 95% confidence interval of both the slope and intercept. I know how to plot 95% ci bands of the OLS slope using lm with the 'predict' function and 'matlines'. Does

Forwarded to: ismtp[samba@samba.org] cc: Comments by: Charles J. Huenke@Admin@SAC Comments: Please offer any input you may have on the issue described below. Thank you. Chuck Huenke Delaware Statistical Analysis Center (302) 739-3680 -------------------------- [Original Message] ------------------------- We received a replacement EFG20 on the referenced

Dear R-experts, The forest.rma() function from the metafor package creates nice forest plots for presenting the results of a meta-analysis. These plots can be annotated for e.g. giving names to the columns. E.g. as in the documentation of the package: data(dat.bcg) ### meta-analysis of the log relative risks using a random-effects model res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg,

Anyone have any luck RMAing a Sipura phone since the Cisco take over? Sipura only has support via email or fax to end users and I haven't gotten a response to either for over 2 months. Linksys Support will jump you through all their scripted hoops to resolve your problem (they hope if they speak with a thick enough accent and make repeat the same steps over and over again that you will just

Hi, for testing if the slope of experimental data differs from a given slope I'm using the function "test_regression_against_slope" (see below). I am now confronted with the problem that I have data which requires a modelII regression (also called reduced major axes regression (RMA) or geometric mean regression). For this I use the function "modelII" (see below). What

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Full_Name: Edward J. Oakeley Version: 1.7.1 OS: Windows XP Submission from: (NULL) (212.47.183.3) This bug occurs when using the (D)COM server to connect to the "expresso" command of the Bioconductor Affy package. It may be a bug of R, (D)COM or Affy ut I will report it here anyway as it feels like an R bug. The Affy package when invoked will read a series of large (10Mb) text files

Hello, I want to use expresso for preprocessing the hgu133a-spikein data from affycompII. But there is an error: > library(affy) > path <- "z:/Microarray/hgu133a-spikein/rawdata" > celFile <- list.celfiles(path=path,full.names=TRUE); > affyBatch <- ReadAffy(filenames=celFile[1:6]); > eset1 <-

Hi together, we received a question about the bioconductor package, maybe anybody could help the guy and I will deliver the message over our forum to him. If this way is allowed ... Regards Knut Here the question: Hello, I have installed R on a linux machine. I have then installed the biocLite.R package from bioconductor. I wanted to install a few other packages - hgu133plus2cdf, rma . I