similar to: Stumped on methods

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

Hi, all-- I wanted to start a (new) thread on R speed/benchmarking. There is a nice R benchmarking overview at http://www.sciviews.org/other/benchmark.htm, along with a free script so you can see how your machine stacks up. Looks like R is substantially faster than S-plus. My problem is this: with 512Mb and an overclocked AMD Athlon XP 1800+, running at 588 SPEC-FP 2000, it still takes me

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 <-

My question is when the object argument of NexthMethod be used? In the following example, weather object argument is used will not affects the result. ### foo=function(x) {UseMethod("foo")} foo.cls1=function(x) { x=x+1;class(x)<-"ncls" NextMethod() } foo.ncls=function(x) { cat("ncls\n") } foo.cls2=function(x) { cat("cls2\n");print(x) }

Hi All, I have microarray data that does not come in a CEL file. Currently it is in the form of columns = individual samples and rows = individual probes. There are about 79 columns and it is in a tab delimited text file. Is there a way to convert this file into an AffyBatch so that I can run expresso with it? Thanks, George

On 02/22/2018 12:07 PM, I?aki ?car wrote: > 2018-02-22 10:29 GMT+01:00 Tomas Kalibera <tomas.kalibera at gmail.com>: >> The example is invoking NextMethod via an anonymous function, which is not >> allowed (see documentation for NextMethod). > Thanks for your response. I definitely missed that bit. > >> Normally one gets a runtime >> error

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]]

>> One clear moral seems to be don't do anything more inside a >> generic function than you really need to do. Keep it *very* >> simple indeed. >> > I recall JMC saying something like, all generic functions > should be one line long; a call to the appropriate UseMethod. It certainly is encouraging to know that others also have been confused by aspects of

Hi, although I've done S3 dispatching for more than a decade now, I think I managed to overlook/avoid the following pitfall when using NextMethod(): If you explicitly pass argument '...' to NextMethod(), you will effectively pass those argument twice to the "next" method! EXAMPLE: foo0 <- function(...) UseMethod("foo0"); foo1 <- function(...)

The example is invoking NextMethod via an anonymous function, which is not allowed (see documentation for NextMethod). Normally one gets a runtime error "'NextMethod' called from an anonymous function", but not here as the anonymous function is called via do.call. I will fix so that there is a runtime error in this case as well, thanks for uncovering this problem. I

On Dec 8, 2011, at 10:03 PM, Nick Lewycky wrote: > Noalias returns, nocapture, SCC refinement, linkonce_odr and > available_externally were added with the goal of making devirtualization > in LLVM happen, but as orthogonal independent optimizations. I think > LLVM should continue with this design. If you want to implement a single > substantial optimization pass, I would suggest

I found writing the following default method the for the generic function "julian" causes R to crash. julian.default <- function(x, ...) { x <- as.Date(x) NextMethod("julian", x, ...) } Here is a test example > m <- as.Date("1972-09-27") + 0:10 > m [1] "1972-09-27" "1972-09-28" "1972-09-29"

I have another problem with NextMethod. Not sure if its related to the last problem. In this example, we have a generic called ff with methods for AsIs and test classes. We call the generic with an object of AsIs class. The corresponding method adds 1 to it and then changes the class to test followed by issuing a NextMethod. However, that results in this error (using R 2.0.0, 2004-10-04

S Programming by Venables and Ripley (page 78) has the example listed at the end of this email. However, I get the following error when I try the example. I don't understand the descriptions of NextMethod on its help page. Could somebody let me know how to fix the error of this example? > test(x) c1 c2 Error in NextMethod() : no method to invoke Calls: test -> test.c1 -> NextMethod

memcpy_fromiovec is moved from net/core/iovec.c to lib/iovec.c. linux/uio.h provides the declaration for memcpy_fromiovec. Include linux/uio.h instead of inux/socket.h for it. Signed-off-by: Asias He <asias at redhat.com> --- drivers/vhost/vhost.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/drivers/vhost/vhost.c b/drivers/vhost/vhost.c index e58cf00..448efe0 100644

memcpy_fromiovec is moved from net/core/iovec.c to lib/iovec.c. linux/uio.h provides the declaration for memcpy_fromiovec. Include linux/uio.h instead of inux/socket.h for it. Signed-off-by: Asias He <asias at redhat.com> --- drivers/vhost/vhost.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/drivers/vhost/vhost.c b/drivers/vhost/vhost.c index e58cf00..448efe0 100644

Hi all, Not sure if this belongs to R-devel or R-package-devel. Anyways... Suppose we have objects of class c("foo", "bar"), and there are two S3 methods c.foo, c.bar. In c.foo, I'm trying to modify the dots and forward the dispatch using NextMethod without any success. This is what I've tried so far: c.foo <- function(..., recursive=FALSE) { dots <-

Configure fails at testing for openib - anyone an idea? Thanks Michaell configure:10034: checking whether to enable OpenIB gen2 support configure:10138: cp conftest.c build && make -d modules CC=gcc -f /home/mhebenst/lustre-2.3.0/build/Makefile LUSTRE_LINUX_CONFIG=/adm in/extra/linux-2.6.32-358.2.1.el6.x86_64.crt1/.config LINUXINCLUDE= -I/usr/local/ofed/3.5/src/compat-rdma-3.5/include

"[.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("[", x) } "[[.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("[[", x) } "$.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("$", x) } > class(x) [1]

R : Copyright 2001, The R Development Core Team Version 1.3.1 (2001-08-31) > tmp <- factor(1:3) > get("print.factor")(tmp) [1] 1 2 3 Levels: 1 2 3 > print.a <- function(x,...) { + print("this is a") + NextMethod("print", x, quote = FALSE, right = TRUE, ...) + } > > get("print.a") function(x,...) { print("this is a")