Closed brooklynnrm closed 1 year ago
@brooklynnrm - what is the error message you receive?
can you also add the output from sessionInfo()?
@cbroeckl The error is below:
organizing dataset replaced 75 of 171 total feature values ( 44 % ) normalizing dataset Error in rc.ramclustr(ramclustObj = ramclustObj, st = st, sr = sr, maxt = maxt, : unused argument (fftempdir = fftempdir)
I am fairly certain this is an artifact of a reorganization of code we recently performed. i would request that you try to install from github, try again, and let me know how it goes.
detach('package:RAMClustR') devtools::install_github("cbroeckl/RAMClustR", dependencies = FALSE)
I just re-installed and tried again. Still getting the error:
Error in rc.ramclustr(ramclustObj = ramclustObj, st = st, sr = sr, maxt = maxt, : unused argument (fftempdir = fftempdir)
alright - just pushed an edit. i think i found the reference causing the problem. Please try again. if this doesn't fix the issue i will ask for input files and will try to replicate the error here first.
detach('package:RAMClustR') devtools::install_github("cbroeckl/RAMClustR", dependencies = FALSE)
Thank you so much for your help! This has fixed the issue!
Hello, I have been trying to use the ramclustr function for deconvolution of an XCMS feature table. I have tried my own data as well as the example data and everything has thrown the error below:
Error in rc.ramclustr(ramclustObj = ramclustObj, st = st, sr = sr, maxt = maxt, : unused argument (fftempdir = fftempdir)
My input is: ure table gc_feature_table<- read.table("E:/Galaxy/Bacarelli - Additional Samples/Galaxy processing files/XCMS_Test_231017_XCMSv3.22.0_Peak.min_Peak.max.txt", sep="\t", header=TRUE)
create mz_time vector
mz_time<- paste(gc_feature_table$mz, gc_featuretable$rt, sep="") mz_time[1:10]
transcribe intensities
t_gc_int<- data.frame(t(gc_feature_table[,10:ncol(gc_feature_table)]))
add mz_time vector to transcribed matrix
t_gc_int_1<- rbind(mz_time,t_gc_int)
add sample_id vector to transcribed matrix
sample_id<- c("sample",rownames(t_gc_int)) t_gc_int_2<- cbind(sample_id,t_gc_int_1) t_gc_int_23 <- t_gc_int_2[1:10,1:20]
write output
setwd("E:/XCMS Projects/RamClustR/") write.table(t_gc_int_23, "XCMS_Test_231018_RAMClustR.csv", sep=",", row.names=FALSE, col.names=FALSE)
library(RAMClustR)
out_file<- "E:/XCMS Projects/RamClustR/" dir.create(out_file) setwd(out_file)
experiment_GC <- defineExperiment(csv = "E:/XCMS Projects/RamClustR/ExpDes.csv")
GC_Clust <- ramclustR(ms = "E:/XCMS Projects/RamClustR/XCMS_Test_231018RAMClustR.csv", featdelim = "", st = 5, ExpDes=experiment_GC, sampNameCol = 1, minModuleSize=1, mzdec=5, fftempdir = NULL)