Open wushaowen1992 opened 2 years ago
Yes. This error is parallel computation related. I wonder where you run the xcmsrokcer? HPC or local computer?
I am runing on a local computer, with 16 cores of CPU and 32 G of memory.
How can I reduce the number of parallel calculation in order to keep it going? Although this will prolong the running time. Thanks.
You can add the following code before the error codes to skip the parallel computation:
BiocParallel::register(BiocParallel::SerialParam(), default = TRUE)
Another option is to use a local version of PMDDA. xcmsrocker is mainly designed for hpc and user need to know how to mapping local path through docker to use their own data. In your case, a local version might be much easier. You could clone this repo: https://github.com/yufree/pmdda
Click 'PMDDA.Rproj' in RStudio to open the project. Then you will need renv
package to reproduce the software environment needed for PMDDA:
install.packages('renv')
renv::restore()
Thanks for this detailed information. I will try to follow the local version.
Hi, I tried to work with both xcmsrocker and local PMDDA project, both have some issues. I tried to use xcmsrocker, with BiocParallel::register(BiocParallel::SerialParam(), default = FALSE), IPO could work. but when I reach to the step, # back up peak list as csv file and xcmsSet object mzrt <- enviGCMS::getmzrt(srm, name = 'srm') I see the srmxset.rds, but no csv file, and an error says: Note: you might want to set/adjust the 'sampclass' of the returned xcmSet object before proceeding with the analysis. Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘featureValues’ for signature ‘"xcmsSet"’ How could I deal with this issue? Thank you.
It's wired. Anyway the csv file could be generated via the srmxset.rds
. You can try the following code:
mzrt<-readRDS('srmxset.rds')
enviGCMS::getmzrt(mzrt,'srm')
Then you should see srmmzrt.csv
.
Hi yufree, I am trying to use this good tool xcmsrocker that you developed and try to repeat your PMDDA workflow, however, when I run the demo data, and reach to the step:
IPO
resultRetcorGroup <- optimizeRetGroup(xset = optimizedXcmsSetObject, params = retcorGroupParameters, plot = F, subdir = NULL)
I always got an error says "Error in unserialize(node$con) : error reading from connection". From the internet, it seems to be a problem with parallel calculation, I wonder if you know how to deal with this issue? Thanks very much for your help.