similar to: Error in WGCNA package

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, 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 Everyone, I am getting the following error message Error: cannot allocate vector of size 2.6 Gb In addition: Warning messages: 1: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see help(memory.size) 2: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see help(memory.size) 3: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see

Hi, I am have a data set of around 43000 probes(rows), and have to calculate correlation matrix. When I run cor function in R, its throwing an error message of RAM shortage which was obvious for such huge number of rows. I am not getting a logical way to cut off this huge number of entities, is there an alternative to pearson correlation or with other dist() methods calculation(euclidean) that

Hola, tengo una serie de datos datExpr, al usar cor() : cor(datExpr ,method = "pearson", use ="pairwise.complete.obs") me da el siguiente error allocMatrix: too many elements specified Trate con "complete.obs", "na.or.complete", y el resto de las opciones para "use", pero siempre me da algun error.  ¿Alguna idea de como puedo hacer que cor() lea

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

Dear All, I am using the plotrix library to plot some matrices. I have a problem: some of my data are outliers, hence using a linear color scale does not work very well (you would see too many cells having a similar, indistinguishable color). See the code snipped at the end of the email. Plotting the logarithm of the data gets the job done, but my problem is that I would like to write in every

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

Good afternoon, After cuting a hierarchical tree using cutree(), how to check correspondances between classes and branches? This is what we do: srndpchc <- hclust(dist(srndpc$x[1:1000,1:3]),method="ward") #creation of hierarchical tree plclust(srndpchc,hmin=20000) #visualisation srndpchc20000 = cutree(srndpchc,h=20000) #returns 4 classes table(srndpchc20000 ) srndclass20000 =

Dear R-Help, I have a clustering problem with hclust that I hope someone can help me with. Consider the classic hclust example: hc <- hclust(dist(USArrests), "ave") plot(hc) I would like to cut the tree up in such a way so as to avoid small clusters, so that we get a minimum number of items in each cluster, and therefore avoid singletons. e.g. in this example, you can see

CRAN (and crantastic) updates this week New packages ------------ * DCGL (1.0) Bao-Hong Liu http://crantastic.org/packages/DCGL Functions for basic differential coexpression analyses: gene filtering, link filtering, DCG (Differentially-Coexpressed Gene) identification and DCL (Differentially-Coexpressed Links) identification.Two algorithms,named DCP and DCe, are provided for

I am in need of someone's help in correlating gene expression. I'm somewhat new to R, and can't seem to find anyone local to help me with what I think is a simple problem. I need to obtain pearson and spearman correlation coefficients, and corresponding p-values for all of the genes in my dataset that correlate to one specific gene of interest. I'm working with mouse Affymetrix

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).

Hi all, I maintain the WGCNA package which at present has nearly 200 functions. In the future there will be more. Curious whether it would be preferable or useful to split the package into a couple different ones with different aims. Obviously, when one calls a function in R, package name spaces have to be traversed to find the matching name - does the speed of this depend on how functions are

Hi all, I encountered a problem when trying to read in an Illumina chip annotation file. The offending file is large, so I zipped it up and posted it at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/tmp/ProbeInfo_Expression.txt.bz2 Executing this: annot = read.table(bzfile("ProbeInfo_Expression.txt.bz2"), comment.char="", sep =

Hi All, is there any effiective and dense/compact method to calculate the mean of a list of - of course coincident - matrices on an element by element basis? The resulting matrix' [i, j]-th element is the mean of the list's matrices' [i, j]-th elements respectively... Iterating by for statement is quite straightforward, but I am seeking for a more elegant solution, and my attempt with

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",

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.

Hi Friends, I am trying to write a shell script which can merge the 2 columns into 3rd one on Centos 5. The file is very long around 31200 rows having around 1370 unique groups and around 12000 unique user-names. The 1st column is the groupname and then 2nd column is the user-name. 1st Column (Groupname) 2nd Column (username) admin ankush

Hello, I have a self-defined function to be computed on each column in a matrix. The basic idea is to ignore the elements that have value of 0 during computation. I should be able to write my own function but it could be computational expensive, so I'd love to ask if anyone may have suggestions on how to implement it more efficiently. Thanks in advance. For example, there are three