I tried to run the code in Chapter 7 Data mining with R learning with case study book but I got an error in following line:
rankWorkflows(svm, maxs = TRUE)
The error was:
Error in as.character.default(X[[i]], ...) : no method for coercing
this S4 class to a vector
Then I searched on the internet and found following solution:
importMethodsFrom(GenomicRanges, as.data.frame)
and again again I got a new error:
Error: could not find function "importMethodFrom"
I searched a lot but I got nothing :(
You can try using library(sos) to find the packages where your function is located.
library(sos)
findFn("replaceherewithyourfunction")
Based on the answer of #Bea, there does not seem to be a importMethodsFrom anywhere in R. My guess is you found the call in a NAMESPACE file. Those files have different syntax than normal R scripts.
If you want to load a specific function from an R package (rather than all functions from a package), you can use libraryname::functionname instad of functionname in your code. In your case, replace as.data.frame with GenomicRanges::as.data.frame
If this does not work (for example because you don't have as.data.frame anywhere in your code), you can also load the whole GenomicRanges library with library(GenomicRanges)
Related
can someone please help me understand this:
I encountered an error when calling a function from a library, specifically "steinertree" from the "SteinerNet" package. When stepping into the function with debug(steinertree), I see that the error occurs, when the function in turn calls "steinertree3". When I try debug(steinertree3), I get "object 'steinertree3' not found". Similarly, I can get the code for 'steinertree' by typing it in the terminal, but not for 'steinertree3'.
So it seems to me that there are some "higher-level" functions and "hidden" functions in packages. I did eventually find the error by finding a file "steinertree.R" in the package at CRAN, which contains both 'steinertree' and 'steinertree3', but I`m wondering how to properly go about debugging such "hidden" functions.
Here is a simple example:
library(igraph)
library(SteinerNet)
set.seed(1)
g= erdos.renyi.game(n=10,p.or.m=0.2)
plot(g)
steinertree(type= 'KB', terminals= c(1,3), graph= g)
Thank you!
Use triple colon ::: to execute a function that is not exported by the package/namespace:
package:::hidden_function()
I am trying to run a power analysis using a MonteCarlo approach in R.
I have created a function of two parameters that does output a boolean (tested manually for all relevant values of the parameters). I also have run baby-examples of the MonteCarlo function to make sure that I understand it and that it works well.
Yet when I try to run the real thing, I get the following error message:
Error in parse(text = all_funcs_found[i]) : <text>:1:1: unexpected '::'
1: ::
I read through the source code of the MonteCarlo function (which I found here) and found
#loop through non-primitive functions used in func and check from which package they are
for(i in 1:length(all_funcs_found)){
if(environmentName(environment(eval(parse(text=all_funcs_found[i]))))%in%env_names){
packages<-c(packages,env_names[which(env_names==environmentName(environment(eval(parse(text=all_funcs_found[i])))))])
}
}
which doesn't really make sense to me - why should there be a problem there?
Thank you for any ideas.
I found the answer: the function I wrote was calling a function from a specific library in the form libraryname::functionname.
This works OK if you use the function once manually, but makes MonteCarlo break.
I solved the problem by first loading the relevant library, then removing the 'libraryname::' part from the definition of the main function. MonteCarlo then runs just fine.
I'm quite new to R and I got an assignment that includes a sourcecode.
Part of the source code includes the following line:
library(preprocessCore)
Then I have in my source code a definition of the following function:
quantile.normalize.raw.gtex <- function(edata.mat)
{
norm_edata = normalize.quantiles(as.matrix(edata.mat))
rownames(norm_edata) = rownames(edata.mat)
colnames(norm_edata) = colnames(edata.mat)
return(norm_edata)
}
Finally, I have an object being initialized to the output of this function, after sending a predefined parameter:
tissue.edata.qn = quantile.normalize.raw.gtex(tissue.edata)
From what I understand, the library function is supposed to include the function normalize.quantiles, which is called in the function that is defined in my source code.
However, when I run the line library(preprocessCore) I get the following error:
Error in library(preprocessCore) :
there is no package called ‘preprocessCore’
I also tried to run the rest of the code and got the error:
Error in normalize.quantiles(as.matrix(edata.mat)) :
could not find function "normalize.quantiles"
I looked for the preprocessCore online and eventually I tried to write install.packages("preprocessCore"), but I got a warning message that this package is only available in version 3.6.0 of R, even though I checked and this is the version that I have.
If somebody has any idea what the problem is, I will appreciate your help.
Thanks in advance
The preprocessCore package is available in Bioconductor. So, to install it, you need the following lines:
source("http://bioconductor.org/biocLite.R")
biocLite("preprocessCore")
After that, you can load the package using library(preprocessCore)
Hope it helps.
I'm running the following code:
dat1 <- returns
for (j in 1:12) set(dat1, j = j, value = wind(dat1[[j]]))
And getting the following error message:
Error in wind(dat1[[j]]) : could not find function "wind"
My search for a solution mainly involves packages that aren't properly installed. I'm not 100% sure but I think it isn't related to that.
Best
To check if the function is really loaded into the namespace you have to try to
print the function:
print(wind)
Error in print(wind) : object 'wind' not found
You have to look if the package is correctly loaded
library("foo")
Check package dependency in case of error.
I use the findFn-function in sos-package to search for function names. Unfortunately dataset names also appear in the same column:
install.packages("sos")
library(sos)
findFn("wind")
There is a wind function (or dataset name) in packages: gstat, ismev, NPCirc, BAMBI, ggmap, gcookbook, CircOutlier, plotly, and circular.
I am trying to read probes from a dat file, put them in a vector then put the vector into a subset to be able to concatenate more data to it and write it in a CSV file. Here my piece of code:
library(Biobase)
library(affy)
affys <- read.csv("address of my dat file")
affys_vec <- as.vector(affys)[,1]
exprs(eset)[affys_vec,] -> sub.set
write.csv(sub.set,file="subset.csv")
However when I reach to the : exprs(eset)[affys_vec,] -> sub.set
I get the following error message:
** Error in exprs(eset) :
error in evaluating the argument object' in selecting a method for function 'exprs':
Error: object 'eset' not found **
Are there any suggestions please?
Thanks,
pqtm
See the vignette An introduction to Biobase and ExpressionSets available on your computer, once Biobase is installed, as
vignette(package="Biobase", "ExpressionSetIntroduction")
But the idea is that you have created eset by pre-processing some CEL or other vendor-specific files. How you pre-process those depends on what your files are, maybe with affy or oligo or lumi, or from a public repository using a package like ArrayExpress or GEOquery Or perhaps you're using limma and have no need for an expression set.
The Bioconductor web site and mailing list provides a lot more information.