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### Running command:
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### rm -rf SVM2CRM.buildbin-libdir SVM2CRM.Rcheck && mkdir SVM2CRM.buildbin-libdir SVM2CRM.Rcheck && C:\Users\biocbuild\bbs-3.5-bioc\R\bin\R.exe CMD INSTALL --build --merge-multiarch --library=SVM2CRM.buildbin-libdir SVM2CRM_1.8.0.tar.gz >SVM2CRM.Rcheck\00install.out 2>&1 && cp SVM2CRM.Rcheck\00install.out SVM2CRM-install.out && C:\Users\biocbuild\bbs-3.5-bioc\R\bin\R.exe CMD check --library=SVM2CRM.buildbin-libdir --install="check:SVM2CRM-install.out" --force-multiarch --no-vignettes --timings SVM2CRM_1.8.0.tar.gz
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* using log directory 'C:/Users/biocbuild/bbs-3.5-bioc/meat/SVM2CRM.Rcheck'
* using R version 3.4.2 Patched (2017-10-07 r73498)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'SVM2CRM/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'SVM2CRM' version '1.8.0'
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'SVM2CRM' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
cisREfindbed: no visible global function definition for 'as'
createBed: no visible global function definition for 'write.table'
featSelectionWithKmeans: no visible global function definition for
'kmeans'
featSelectionWithKmeans: no visible global function definition for
'dist'
featSelectionWithKmeans: no visible global function definition for
'hclust'
featSelectionWithKmeans: no visible global function definition for
'pdf'
featSelectionWithKmeans: no visible global function definition for
'par'
featSelectionWithKmeans: no visible global function definition for
'axis'
featSelectionWithKmeans: no visible global function definition for
'abline'
featSelectionWithKmeans: no visible global function definition for
'dev.off'
getSignal: no visible global function definition for 'read.table'
getSignal: no visible global function definition for 'as'
plotROC: no visible global function definition for 'predict'
plotROC: no visible global function definition for 'pdf'
plotROC: no visible global function definition for 'dev.off'
predictionGW: no visible global function definition for 'predict'
smoothInputFS: no visible global function definition for 'na.omit'
tuningParametersCombROC: no visible global function definition for
'combn'
tuningParametersCombROC: no visible global function definition for
'txtProgressBar'
tuningParametersCombROC: no visible global function definition for
'setTxtProgressBar'
Undefined global functions or variables:
abline as axis combn dev.off dist hclust kmeans na.omit par pdf
predict read.table setTxtProgressBar txtProgressBar write.table
Consider adding
importFrom("grDevices", "dev.off", "pdf")
importFrom("graphics", "abline", "axis", "par")
importFrom("methods", "as")
importFrom("stats", "dist", "hclust", "kmeans", "na.omit", "predict")
importFrom("utils", "combn", "read.table", "setTxtProgressBar",
"txtProgressBar", "write.table")
to your NAMESPACE file (and ensure that your DESCRIPTION Imports field
contains 'methods').
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking installed files from 'inst/doc' ... OK
* checking files in 'vignettes' ... OK
* checking examples ...
** running examples for arch 'i386' ... ERROR
Running examples in 'SVM2CRM-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: predictionGW
> ### Title: Perform prediction of cis-regulatory elements genome-wide
> ### Aliases: predictionGW predictionGW
> ### Keywords: prediction, saveoutput,createbed
>
> ### ** Examples
>
> library("GenomicRanges")
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: GenomeInfoDb
> library("SVM2CRMdata")
>
> setwd(system.file("data",package="SVM2CRMdata"))
> load("CD4_matrixInputSVMbin100window1000.rda")
> completeTABLE<-CD4_matrixInputSVMbin100window1000
>
> new.strings<-gsub(x=colnames(completeTABLE[,c(6:ncol(completeTABLE))]),pattern="CD4.",replacement="")
> new.strings<-gsub(new.strings,pattern=".norm.w100.bed",replacement="")
> colnames(completeTABLE)[c(6:ncol(completeTABLE))]<-new.strings
>
> #list_file<-grep(dir(),pattern=".sort.txt",value=TRUE)
>
> #train_positive<-getSignal(list_file,chr="chr1",reference="p300.distal.fromTSS.txt",win.size=500,bin.size=100,label1="enhancers")
> #train_negative<-getSignal(list_file,chr="chr1",reference="random.region.hg18.nop300.txt",win.size=500,bin.size=100,label1="not_enhancers")
> setwd(system.file("data",package="SVM2CRMdata"))
> load("train_positive.rda")
> load("train_negative.rda")
>
> training_set<-rbind(train_positive,train_negative)
> #the colnames of the training set should be the same of data_enhancer_svm
> colnames(training_set)[c(5:ncol(training_set))]<-gsub(x=gsub(x=colnames(training_set[,c(5:ncol(training_set))]),pattern="sort.txt.",replacement=""),pattern="CD4.",replacement="")
>
>
> setwd(system.file("extdata", package = "SVM2CRMdata"))
> data_level2 <- read.table(file = "GSM393946.distal.p300fromTSS.txt",sep = "\t", stringsAsFactors = FALSE)
> data_level2<-data_level2[data_level2[,1]=="chr1",]
>
> DB <- data_level2[, c(1:3)]
> colnames(DB)<-c("chromosome","start","end")
>
> label <- "p300"
>
> table.final.overlap<-findFeatureOverlap(query=completeTABLE,subject=DB,select="all")
>
> data_enhancer_svm<-createSVMinput(inputpos=table.final.overlap,inputfull=completeTABLE,label1="enhancers",label2="not_enhancers")
> colnames(data_enhancer_svm)[c(5:ncol(data_enhancer_svm))]<-gsub(gsub(x=colnames(data_enhancer_svm[,c(5:ncol(data_enhancer_svm))]),pattern="CD4.",replacement=""),pattern=".norm.w100.bed",replacement="")
>
> listcolnames<-c("H2AK5ac","H2AK9ac","H3K23ac","H3K27ac","H3K27me3","H3K4me1","H3K4me3")
>
> dftotann<-smoothInputFS(train_positive[,c(6:ncol(train_positive))],listcolnames,k=20)
[1] "H2AK5ac"
[1] "rename"
[1] "H2AK9ac"
[1] "rename"
[1] "H3K23ac"
[1] "rename"
[1] "H3K27ac"
[1] "rename"
[1] "H3K27me3"
[1] "rename"
[1] "H3K4me1"
[1] "rename"
[1] "H3K4me3"
[1] "rename"
>
>
> results<-featSelectionWithKmeans(dftotann,5)
[1] "H2AK5ac_1"
[1] "H2AK9ac_1"
[1] "H3K23ac_1"
[1] "H3K27ac_1"
[1] "H3K27me3_1"
[1] "H3K4me1_1"
[1] "H3K4me3_1"
[1] "H2AK5ac_1"
[1] "H2AK9ac_1"
[1] "H3K23ac_1"
[1] "H3K27ac_1"
[1] "H3K27me3_1"
[1] "H3K4me1_1"
[1] "H3K4me3_1"
>
> resultsFS<-results[[7]]
>
>
> resultsFSfilter<-resultsFS[which(resultsFS[,2]>median(resultsFS[,2])),]
>
> resultsFSfilterICRR<-resultsFSfilter[which(resultsFSfilter[,3]<0.50),]
>
> listHM<-resultsFSfilterICRR[,1]
> listHM<-gsub(gsub(listHM,pattern="_.",replacement=""),pattern="CD4.",replacement="")
>
> selectFeature<-grep(x=colnames(training_set[,c(6:ncol(training_set))]),pattern=paste(listHM,collapse="|"),value=TRUE)
>
> colSelect<-c("chromosome","start","end","label",selectFeature)
> training_set<-training_set[,colSelect]
>
> vecS <- c(2:length(listHM))
> typeSVM <- c(0, 6, 7)[1]
> costV <- c(0.001, 0.01, 0.1, 1, 10, 100, 1000)[6]
> wlabel <- c("not_enhancer", "enhancer")
> infofile<-data.frame(a=c(paste(listHM,"signal",sep=".")))
> infofile[,1]<-gsub(gsub(x=infofile[,1],pattern="CD4.",replacement=""),pattern=".sort.bed",replacement="")
>
> tuningTAB <- tuningParametersCombROC(training_set = training_set, typeSVM = typeSVM, costV = costV,different.weight="TRUE", vecS = vecS[1],pcClass=100,ncClass=400,infofile)
[1] "last comparison"
[1] 3 2
[1] 3 2
[1] "k-fold-validation in all combination"
[1] "H3K27ac.signal" "H3K4me1.signal"
[1] "H3K27ac.signal" "H3K4me3.signal"
[1] "H3K4me1.signal" "H3K4me3.signal"
>
> tuningTABfilter<-tuningTAB[tuningTAB$fscore<0.95,]
> #row_max_fscore<-which.max(tuningTABfilter[tuningTABfilter$nHM >2,"fscore"])
> row_max_fscore<-which.max(tuningTABfilter[,"fscore"])
> listHM_prediction<-gsub(tuningTABfilter[row_max_fscore,4],pattern="//",replacement="|")
>
> columnPR<-grep(colnames(training_set),pattern=paste(listHM_prediction,collapse="|"),value=TRUE)
>
> predictionGW(training_set=training_set,data_enhancer_svm=data_enhancer_svm, listHM=columnPR,pcClass.string="enhancers",nClass.string="not_enhancers",pcClass=100,ncClas=400,cost=100,type=0,"prediction_enhancers_CD4_results_cost=100_type=0")
Error in wilcox.test.default(pred[obs == 1], pred[obs == 0], alternative = "great") :
not enough (finite) 'x' observations
Calls: predictionGW ... plotROC -> roc.area -> wilcox.test -> wilcox.test.default
Execution halted
** running examples for arch 'x64' ... OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 ERROR, 1 NOTE
See
'C:/Users/biocbuild/bbs-3.5-bioc/meat/SVM2CRM.Rcheck/00check.log'
for details.
