similar to: What is preferable - a single large package or a few smaller packages?

Hi all, I'm trying to set up the Windows Rtools toolset for building packages with compiled code. I installed for Windows R-3.4.3 from CRAN and installed Rtools-3.4 in a custom location M:\R\R-3.4.3 and M:\R\Rtools-3.4 Following the instructions, in shell, I set Path=M:\R\Rtools-3.4\bin;M:\R\Rtools-3.4\gcc-4.6.3\bin;M:\R\R-3.4.3\bin;... (the ... are other paths irrelevant for R/Rtools).

Hello fellow R users, I am currently learning to use R, so please forgive me if there is an obvious explanation for the following problem. My goal is to perform WGCNA on a dataset of 19776 genes, so I opted to follow the block-wise network construction (Section 2c) in the WGCNA R Tutorial by Peter Langfelder and Steve Horvath. I ended up with 10 blocks and am able to plot the dendrograms and

Hi all, a user contacted me about a segfault when installing WGCNA package dowloaded from CRAN. I also see a segfault like that on certain installs of R. The package passes all CRAN checks, so presumably this has something to do with the R installation or environment. The R versions here are not the newest but I would guess that this is not an R version issue. I'm attaching two

It seems like many of the multi-threaded BLASes have some sort of fundamental problem preventing use in the way Juan suggests: - Dirk's vignette states that ATLAS "fixes the number of cores used at compile-time and cannot vary this setting at run-time", so any user-friendly implementation for R would have to compile ATLAS for 1-16 threads to allow the user to switch at run-time.

Please pardon my ignorance, but doesn't OpenBLAS still not always play nicely with multi-threaded OpenMP? (for example, don't race conditions sometimes crop up)? If so, it might be nice to have the ability to temporarily disable multi-threaded OpenMP (effectively: omp_set_num_threads(1)) for the duration of operations using OpenBLAS. Regards Ben > Julia using OpenBLAS is *very*

Julia Programming Language uses also OpenBlas, and it is actively maintained with bugs being fixed as I have checked it out: http://www.openblas.net/Changelog.txt So I still see it ok to be included as an options(...) feature (by default off, just for safety), over other Blas libraries. R could not use Intel MKL for legal reasons (I think), because as long that R ships with GPL libraries,

I didn't do the compile; is there a way to check whether that was used? If not, I'll inquire with our sysadmin and report back. In any case, my suggestion was motivated by the fact that some parts of R use OpenMP while others do not, in the hope that the former could have their OpenBLAS omelet without breaking the OpenMP eggs, so to speak. On 01/09/2018 06:41 PM, Keith O'Hara

Thanks Keith. We checked, and indeed libopenblas is not linked against libomp nor libgomp. We suspect this is because we used conda to install R and OpenBLAS. So I guess we should be barking up the conda tree instead? By the way, I also noticed on my home machine (Ubuntu), /usr/lib/libopenblas.so.0 is also not linked against those, for what that's worth. Regards, Ben On 01/10/2018 12:04

Dear all, I've been trying to find how to compare tow different heatmaps but I'm having trouble getting the colors bar to be the same. I'm doing something like the following: library(gplots) dat<-cor(matrix(rnorm(100, m=10), nrow=10)) mat<-cor(matrix(rnorm(100), nrow=10)) dev.new() heatmap.2(mat, Rowv=NA, Colv=NA, col=redgreen(75), symm=TRUE, trace="none",

I can confirm the behaviour that you report.? Usually I put Rtools in c:\programs\Rtools and modify the path accordingly. Recently (don't recall for how long) I have encountered the same problems as you have and I have resorted to moving Rtools to c:\Rtools I have no idea as how to proceed; perhaps it could be worth trying an older version of Rtools (though that may cause other problems).

Hi, I'm running a tutorial ("Meta-analyses of data from two (or more) microarray data sets"), which use wgcna package. I have an error in the function modulePreservation (it is below). I'm using R2.13 Can you help me? Do you know, what is happens? Thanks Raquel multiExpr = list(A = list(data=t(badea)),B = list(data=t(mayo))) # two independent datasets (dim = 13447 x 36) mp =

Hi R-devel list, OpenBLAS is readily available for unix-likes: https://cloud.r-project.org/web/packages/gcbd/vignettes/gcbd.pdf However, my questions are: 1) Would R-devel consider using OpenBLAS for the main distribution of R for all platforms including Windows? 2) If so, would R-devel set the default multi-thread level to the number of (real) cores on a machine? My sense is there're a

I am now getting the occasional complaint about survival routines that are not able to handle big data.?? I looked in the manuals to try and update my understanding of max vector size, max matrix, max data set, etc; but it is either not there or I missed it (the latter more likely).?? Is it still .Machine$integer.max for everything??? Will that change??? Found where? I am going to need to go

Dear R-helpers, This may sound simple to you, but I'm a beginner in this, so please be forgiving. I have a following problem: two analytes were measured in patient's blood on 4 occasions: ProteinA and ProteinB. How to correctly evaluate correlation between ProteinA and ProteinB? I tried: x <- data.frame(Patient.ID=rep(1:10, each=4), Visit=rep(c(1:4),10), ProteinA=rnorm(m=10,

On Sat, Dec 16, 2017 at 7:41 PM, Kenny Bell <kmbell56 at gmail.com> wrote: > It seems like many of the multi-threaded BLASes have some sort of > fundamental problem preventing use in the way Juan suggests: > > - Dirk's vignette states that ATLAS "fixes the number of cores used at > compile-time and cannot vary this setting at run-time", so any > user-friendly

Hello, I am working on a backup script using rsync and have a question. Rather than doing a single rsync of /home/ I have set my script up to loop over /etc/passwd and do a seperate rsync of each user home dir (/home/user1, /home/user2) etc. In the end, I should have the exact same backup either way. However I feel safest doing it as multiple rsyncs (one for each user). I am doing this

First, please read WGCNA FAQ at https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/faq.html regarding using RNA-seq and other count data. Second, if you insist on using WGCNA on raw count data (which I don't recommend), use something like storage.mode(datExpr) = "double" and try again. Peter On Sun, Jul 9, 2017 at 2:29 AM, Ankush Sharma <ankush.sak at

Hi everyone, I’m looking for a clever bit of code to replace NA’s with a specific score depending on an indicator variable. I can see how to do it using lots of if statements but I’m sure there most be a neater, better way of doing it. Any ideas at all will be much appreciated, I’m dreading coding up all those if statements!!!!! My problem is as follows: I have a data set with

Dear all , I would like to reconstruct coexpression networks from proteomic count data having integer values. Some internal function doesn't like to work well with integers. How can this error be rectified? > adjacency = adjacency(datExpr, power = softPower, type = "signed"); Error in cor(datExpr, use = "p") : REAL() can only be applied to a 'numeric', not a

Do those issues still arise when OpenBLAS is compiled with USE_OPENMP=1 ? Keith > On Jan 9, 2018, at 6:03 PM, Benjamin Tyner <btyner at gmail.com> wrote: > > Please pardon my ignorance, but doesn't OpenBLAS still not always play nicely with multi-threaded OpenMP? (for example, don't race conditions sometimes crop up)? If so, it might be nice to have the ability to