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CHECK report for seq2pathway on merida2

This page was generated on 2019-04-09 13:31:01 -0400 (Tue, 09 Apr 2019).

Package 1459/1703HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
seq2pathway 1.15.0
Xinan Yang with contribution from Zhezhen Wang
Snapshot Date: 2019-04-08 17:01:18 -0400 (Mon, 08 Apr 2019)
URL: https://git.bioconductor.org/packages/seq2pathway
Branch: master
Last Commit: 22e9924
Last Changed Date: 2019-04-07 15:28:41 -0400 (Sun, 07 Apr 2019)
malbec2 Linux (Ubuntu 18.04.2 LTS) / x86_64  OK  OK  ERROR 
tokay2 Windows Server 2012 R2 Standard / x64  OK  OK  ERROR  OK 
celaya2 OS X 10.11.6 El Capitan / x86_64  OK  OK  ERROR  OK 
merida2 OS X 10.11.6 El Capitan / x86_64  OK  OK [ ERROR ] OK 

Summary

Package: seq2pathway
Version: 1.15.0
Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:seq2pathway.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings seq2pathway_1.15.0.tar.gz
StartedAt: 2019-04-09 03:39:55 -0400 (Tue, 09 Apr 2019)
EndedAt: 2019-04-09 03:44:37 -0400 (Tue, 09 Apr 2019)
EllapsedTime: 282.2 seconds
RetCode: 1
Status:  ERROR 
CheckDir: seq2pathway.Rcheck
Warnings: NA

Command output

##############################################################################
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###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:seq2pathway.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings seq2pathway_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.9-bioc/meat/seq2pathway.Rcheck’
* using R Under development (unstable) (2018-11-27 r75683)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘seq2pathway/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘seq2pathway’ version ‘1.15.0’
* 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 for sufficient/correct file permissions ... OK
* checking whether package ‘seq2pathway’ 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
* 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 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
FAIME_EmpiricalP: no visible global function definition for ‘data’
FAIME_EmpiricalP: no visible binding for global variable
  ‘gencode_coding’
FisherTest_GO_BP_MF_CC: no visible global function definition for
  ‘data’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_BP_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_MF_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_CC_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘Des_BP_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘Des_MF_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘Des_CC_list’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_GENCODE_df_hg_v20’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_GENCODE_df_hg_v19’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_GENCODE_df_mm_vM4’
FisherTest_GO_BP_MF_CC: no visible binding for global variable
  ‘GO_GENCODE_df_mm_vM1’
FisherTest_GO_BP_MF_CC: no visible global function definition for
  ‘fisher.test’
FisherTest_GO_BP_MF_CC: no visible global function definition for
  ‘p.adjust’
FisherTest_MsigDB: no visible global function definition for ‘data’
FisherTest_MsigDB: no visible binding for global variable
  ‘Msig_GENCODE_df_hg_v20’
FisherTest_MsigDB: no visible binding for global variable
  ‘Msig_GENCODE_df_hg_v19’
FisherTest_MsigDB: no visible binding for global variable
  ‘Msig_GENCODE_df_mm_vM4’
FisherTest_MsigDB: no visible binding for global variable
  ‘Msig_GENCODE_df_mm_vM1’
FisherTest_MsigDB: no visible global function definition for
  ‘fisher.test’
FisherTest_MsigDB: no visible global function definition for ‘p.adjust’
KSrank: no visible global function definition for ‘ks.test’
KSrank_EmpiricalP: no visible global function definition for ‘data’
KSrank_EmpiricalP: no visible binding for global variable
  ‘gencode_coding’
KSrank_EmpiricalP: no visible global function definition for ‘ks.test’
Normalize_F: no visible global function definition for ‘head’
cumulativerank_EmpiricalP: no visible global function definition for
  ‘data’
cumulativerank_EmpiricalP: no visible binding for global variable
  ‘gencode_coding’
gene2pathway_test: no visible global function definition for ‘data’
gene2pathway_test: no visible binding for global variable ‘GO_BP_list’
gene2pathway_test: no visible binding for global variable ‘GO_MF_list’
gene2pathway_test: no visible binding for global variable ‘GO_CC_list’
gene2pathway_test: no visible binding for global variable ‘Des_BP_list’
gene2pathway_test: no visible binding for global variable ‘Des_CC_list’
gene2pathway_test: no visible binding for global variable ‘Des_MF_list’
plotTop10: no visible binding for global variable ‘Fisher_odds’
plotTop10: no visible binding for global variable ‘FDR’
plotTop10: no visible global function definition for ‘barplot’
plotTop10: no visible global function definition for ‘lines’
plotTop10: no visible global function definition for ‘text’
plotTop10: no visible global function definition for ‘abline’
rungene2pathway_EmpiricalP: no visible global function definition for
  ‘txtProgressBar’
rungene2pathway_EmpiricalP: no visible global function definition for
  ‘setTxtProgressBar’
runseq2gene: no visible global function definition for ‘write.table’
runseq2gene: no visible global function definition for ‘read.table’
runseq2pathway: no visible global function definition for ‘data’
runseq2pathway: no visible binding for global variable ‘GO_BP_list’
runseq2pathway: no visible binding for global variable ‘GO_MF_list’
runseq2pathway: no visible binding for global variable ‘GO_CC_list’
runseq2pathway: no visible binding for global variable ‘Des_BP_list’
runseq2pathway: no visible binding for global variable ‘Des_CC_list’
runseq2pathway: no visible binding for global variable ‘Des_MF_list’
runseq2pathway: no visible global function definition for ‘write.table’
runseq2pathway: no visible global function definition for ‘read.table’
Undefined global functions or variables:
  Des_BP_list Des_CC_list Des_MF_list FDR Fisher_odds GO_BP_list
  GO_CC_list GO_GENCODE_df_hg_v19 GO_GENCODE_df_hg_v20
  GO_GENCODE_df_mm_vM1 GO_GENCODE_df_mm_vM4 GO_MF_list
  Msig_GENCODE_df_hg_v19 Msig_GENCODE_df_hg_v20 Msig_GENCODE_df_mm_vM1
  Msig_GENCODE_df_mm_vM4 abline barplot data fisher.test gencode_coding
  head ks.test lines p.adjust read.table setTxtProgressBar text
  txtProgressBar write.table
Consider adding
  importFrom("graphics", "abline", "barplot", "lines", "text")
  importFrom("stats", "fisher.test", "ks.test", "p.adjust")
  importFrom("utils", "data", "head", "read.table", "setTxtProgressBar",
             "txtProgressBar", "write.table")
to your NAMESPACE file.
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... WARNING
Codoc mismatches from documentation object 'plotTop10':
plotTop10
  Code: function(res, fdr = 0.05, or = 2, myfileID = NULL)
  Docs: function(res, fdr = 0.01, or = 1.5)
  Argument names in code not in docs:
    myfileID
  Mismatches in argument default values:
    Name: 'fdr' Code: 0.05 Docs: 0.01
    Name: 'or' Code: 2 Docs: 1.5

* checking Rd \usage sections ... WARNING
Documented arguments not in \usage in documentation object 'plotTop10':
  ‘myfileID’

Functions with \usage entries need to have the appropriate \alias
entries, and all their arguments documented.
The \usage entries must correspond to syntactically valid R code.
See chapter ‘Writing R documentation files’ in the ‘Writing R
Extensions’ manual.
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘seq2pathway-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: runseq2pathway
> ### Title: An function to perform the runseq2pathway algorithm(s).
> ### Aliases: runseq2pathway
> ### Keywords: methods
> 
> ### ** Examples
> 
> 	data(Chipseq_Peak_demo)
> 	require(seq2pathway.data)
Loading required package: seq2pathway.data
> 	data(MsigDB_C5, package="seq2pathway.data")
>   #generate a demo GSA.genesets object
> 	demoDB <- MsigDB_C5
> 	x=10
> 	for(i in 1:3) demoDB[[i]]<-MsigDB_C5[[i]][1:x]
>        res3=runseq2pathway(inputfile=Chipseq_Peak_demo,
+ 		genome="hg19", search_radius=100, promoter_radius=50, promoter_radius2=0,
+ 		FAIMETest=TRUE, FisherTest=FALSE,  
+ 		DataBase=demoDB, min_Intersect_Count=1)	
[1] "python process start: 2019-04-09 03:43:39.080066"
[2] "Load Reference"                                  
[3] "Check Reference files"                           
[4] "fixed reference done: 2019-04-09 03:44:28.327052"
[5] "Start Annotation"                                
[6] "Finish Annotation"                               
[7] "python process end: 2019-04-09 03:44:28.330627"  
[1] "Start test.............."
Warning: 5 or fewer samples, this method of probe collapse is unreliable...
...Running anyway, but we suggest trying another method (for example, *mean*).
[1] "Peak_Gene_Collapse....... done"
 ----------- FAILURE REPORT -------------- 
 --- failure: the condition has length > 1 ---
 --- srcref --- 
: 
 --- package (from environment) --- 
seq2pathway
 --- call from context --- 
runseq2pathway(inputfile = Chipseq_Peak_demo, genome = "hg19", 
    search_radius = 100, promoter_radius = 50, promoter_radius2 = 0, 
    FAIMETest = TRUE, FisherTest = FALSE, DataBase = demoDB, 
    min_Intersect_Count = 1)
 --- call from argument --- 
if (DataBase %in% c("GOterm", "BP", "CC", "MF")) {
    if (DataBase %in% c("GOterm", "BP")) {
        GO_BP_FAIME <- rungene2pathway(dat = dat_CP, gsmap = GO_BP_list, 
            alpha = alpha, logCheck = logCheck, method = "FAIME", 
            na.rm = na.rm)
        GO_BP_FAIME_N <- Normalize_F(input = GO_BP_FAIME)
        GO_BP_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
            gsmap = GO_BP_list, alpha = alpha, logCheck = logCheck, 
            method = "FAIME", B = B, na.rm = na.rm)
        GO_BP_N_P <- merge(GO_BP_FAIME_N, GO_BP_FAIME_Pvalue, 
            by = "row.names", all = TRUE)
        rownames(GO_BP_N_P) <- GO_BP_N_P$Row.names
        GO_BP_N_P <- GO_BP_N_P[, -1]
        for (i in 1:nrow(GO_BP_N_P)) {
            intsect <- intersect(toupper(rownames(dat_CP)), toupper(unlist(GO_BP_list[names(GO_BP_list) == 
                rownames(GO_BP_N_P)[i]])))
            GO_BP_N_P$Intersect_Count[i] <- length(intsect)
            GO_BP_N_P$Intersect_gene[i] <- paste(intsect, collapse = " ")
            GO_BP_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                intsect, c(1)]), collapse = " ")
            rm(intsect)
            GO_BP_N_P$Des[i] <- as.character(Des_BP_list[which(names(Des_BP_list) == 
                rownames(GO_BP_N_P)[i])])
        }
        GO_BP_N_P <- GO_BP_N_P[GO_BP_N_P$Intersect_Count >= min_Intersect_Count, 
            ]
        GO_BP_N_P <- GO_BP_N_P[, c(ncol(GO_BP_N_P), 1:(ncol(GO_BP_N_P) - 
            1))]
        n.list = n.list + 1
        gene2pathway_result[[n.list]] <- GO_BP_N_P
        names(gene2pathway_result)[n.list] <- c("GO_BP")
    }
    if (DataBase %in% c("GOterm", "MF")) {
        GO_MF_FAIME <- rungene2pathway(dat = dat_CP, gsmap = GO_MF_list, 
            alpha = alpha, logCheck = logCheck, method = "FAIME", 
            na.rm = na.rm)
        GO_MF_FAIME_N <- Normalize_F(input = GO_MF_FAIME)
        GO_MF_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
            gsmap = GO_MF_list, alpha = alpha, logCheck = logCheck, 
            method = "FAIME", B = B, na.rm = na.rm)
        GO_MF_N_P <- merge(GO_MF_FAIME_N, GO_MF_FAIME_Pvalue, 
            by = "row.names", all = TRUE)
        rownames(GO_MF_N_P) <- GO_MF_N_P$Row.names
        GO_MF_N_P <- GO_MF_N_P[, -1]
        for (i in 1:nrow(GO_MF_N_P)) {
            intsect <- intersect(toupper(rownames(dat_CP)), toupper(unlist(GO_MF_list[names(GO_MF_list) == 
                rownames(GO_MF_N_P)[i]])))
            GO_MF_N_P$Intersect_Count[i] <- length(intsect)
            GO_MF_N_P$Intersect_gene[i] <- paste(intsect, collapse = " ")
            GO_MF_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                intsect, c(1)]), collapse = " ")
            rm(intsect)
            GO_MF_N_P$Des[i] <- as.character(Des_MF_list[which(names(Des_MF_list) == 
                rownames(GO_MF_N_P)[i])])
        }
        GO_MF_N_P <- GO_MF_N_P[GO_MF_N_P$Intersect_Count >= min_Intersect_Count, 
            ]
        GO_MF_N_P <- GO_MF_N_P[, c(ncol(GO_MF_N_P), 1:(ncol(GO_MF_N_P) - 
            1))]
        n.list = n.list + 1
        gene2pathway_result[[n.list]] <- GO_MF_N_P
        names(gene2pathway_result)[n.list] <- c("GO_MF")
    }
    if (DataBase %in% c("GOterm", "CC")) {
        GO_CC_FAIME <- rungene2pathway(dat = dat_CP, gsmap = GO_CC_list, 
            alpha = alpha, logCheck = logCheck, method = "FAIME", 
            na.rm = na.rm)
        GO_CC_FAIME_N <- Normalize_F(input = GO_CC_FAIME)
        GO_CC_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
            gsmap = GO_CC_list, alpha = alpha, logCheck = logCheck, 
            method = "FAIME", B = B, na.rm = na.rm)
        GO_CC_N_P <- merge(GO_CC_FAIME_N, GO_CC_FAIME_Pvalue, 
            by = "row.names", all = TRUE)
        rownames(GO_CC_N_P) <- GO_CC_N_P$Row.names
        GO_CC_N_P <- GO_CC_N_P[, -1]
        for (i in 1:nrow(GO_CC_N_P)) {
            intsect <- intersect(toupper(rownames(dat_CP)), toupper(unlist(GO_CC_list[names(GO_CC_list) == 
                rownames(GO_CC_N_P)[i]])))
            GO_CC_N_P$Intersect_Count[i] <- length(intsect)
            GO_CC_N_P$Intersect_gene[i] <- paste(intsect, collapse = " ")
            GO_CC_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                intsect, c(1)]), collapse = " ")
            rm(intsect)
            GO_CC_N_P$Des[i] <- as.character(Des_CC_list[which(names(Des_CC_list) == 
                rownames(GO_CC_N_P)[i])])
        }
        GO_CC_N_P <- GO_CC_N_P[GO_CC_N_P$Intersect_Count >= min_Intersect_Count, 
            ]
        GO_CC_N_P <- GO_CC_N_P[, c(ncol(GO_CC_N_P), 1:(ncol(GO_CC_N_P) - 
            1))]
        n.list = n.list + 1
        gene2pathway_result[[n.list]] <- GO_CC_N_P
        names(gene2pathway_result)[n.list] <- c("GO_CC")
    }
} else {
    dat_FAIME <- rungene2pathway(dat = dat_CP, gsmap = DataBase, 
        alpha = alpha, logCheck = logCheck, method = "FAIME", 
        na.rm = na.rm)
    N_FAIME <- Normalize_F(input = dat_FAIME)
    dat_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
        gsmap = DataBase, alpha = alpha, logCheck = logCheck, 
        method = "FAIME", B = B, na.rm = na.rm)
    N_FAIME <- as.matrix(N_FAIME)
    dat_FAIME_Pvalue <- as.matrix(dat_FAIME_Pvalue)
    DB_N_P <- cbind(N_FAIME, as.matrix(dat_FAIME_Pvalue[match(rownames(N_FAIME), 
        rownames(dat_FAIME_Pvalue)), ]))
    colnames(DB_N_P) <- c("score2pathscore_Normalized", "score2pathscore_Pvalue")
    DB_N_P <- as.data.frame(DB_N_P)
    for (i in 1:nrow(DB_N_P)) {
        if (class(DataBase) == "GSA.genesets") {
            intsect <- intersect(toupper(rownames(dat_CP)), toupper(unlist(DataBase$genesets[which(DataBase$geneset.names == 
                rownames(DB_N_P)[i])])))
        }
        else if (class(DataBase) == "list") {
            intsect <- intersect(toupper(rownames(dat_CP)), toupper(unlist(DataBase[names(DataBase) == 
                rownames(DB_N_P)[i]])))
        }
        DB_N_P$Intersect_Count[i] <- length(intsect)
        DB_N_P$Intersect_gene[i] <- paste(intsect, collapse = " ")
        DB_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
            intsect, c(1)]), collapse = " ")
        rm(intsect)
        if (class(DataBase) == "GSA.genesets") {
            DB_N_P$Des[i] <- as.character(DataBase$geneset.descriptions[which(DataBase$geneset.names == 
                rownames(DB_N_P)[i])])
        }
    }
    DB_N_P <- DB_N_P[DB_N_P$Intersect_Count >= min_Intersect_Count, 
        ]
    gene2pathway_result <- DB_N_P[, c(ncol(DB_N_P), 1:(ncol(DB_N_P) - 
        1))]
}
 --- R stacktrace ---
where 1: runseq2pathway(inputfile = Chipseq_Peak_demo, genome = "hg19", 
    search_radius = 100, promoter_radius = 50, promoter_radius2 = 0, 
    FAIMETest = TRUE, FisherTest = FALSE, DataBase = demoDB, 
    min_Intersect_Count = 1)

 --- value of length: 3 type: logical ---
[1] FALSE FALSE FALSE
 --- function from context --- 
function (inputfile, search_radius = 150000, promoter_radius = 200, 
    promoter_radius2 = 100, genome = c("hg38", "hg19", "mm10", 
        "mm9"), adjacent = FALSE, SNP = FALSE, PromoterStop = FALSE, 
    NearestTwoDirection = TRUE, UTR3 = FALSE, DataBase = c("GOterm"), 
    FAIMETest = FALSE, FisherTest = TRUE, collapsemethod = c("MaxMean", 
        "function", "ME", "maxRowVariance", "MinMean", "absMinMean", 
        "absMaxMean", "Average"), alpha = 5, logCheck = FALSE, 
    B = 100, na.rm = FALSE, min_Intersect_Count = 5) 
{
    options(warn = -1)
    if (missing(inputfile)) {
        stop("please give the input file")
    }
    if (!class(inputfile) %in% c("data.frame", "GRanges")) {
        stop("please check the format of input file")
    }
    if (missing(DataBase)) {
        DataBase = "GOterm"
    }
    if (missing(FAIMETest)) {
        FAIMETest = FALSE
    }
    if (missing(FisherTest)) {
        FisherTest = TRUE
    }
    if (missing(genome)) {
        genome = "hg19"
    }
    if (missing(search_radius)) {
        search_radius = 150000
    }
    if (missing(promoter_radius)) {
        promoter_radius = 200
    }
    if (missing(promoter_radius2)) {
        promoter_radius2 = 100
    }
    if (missing(SNP)) {
        SNP = "False"
    }
    if (missing(adjacent)) {
        adjacent = "False"
    }
    if (missing(PromoterStop)) {
        PromoterStop = "False"
    }
    if (missing(NearestTwoDirection)) {
        NearestTwoDirection = "True"
    }
    if (missing(UTR3)) {
        UTR3 = "False"
    }
    if (missing(collapsemethod)) {
        collapsemethod = "MaxMean"
    }
    if (missing(B)) {
        B = 100
    }
    if (missing(alpha)) {
        alpha = 5
    }
    if (missing(logCheck)) {
        logCheck = FALSE
    }
    if (missing(na.rm)) {
        na.rm = FALSE
    }
    if (missing(min_Intersect_Count)) {
        min_Intersect_Count = 5
    }
    if (SNP %in% c("T", "TRUE", "True", TRUE)) {
        SNP = "True"
    }
    if (SNP %in% c("F", "FALSE", "False", FALSE)) {
        SNP = "False"
    }
    if (PromoterStop %in% c("T", "TRUE", "True", TRUE)) {
        PromoterStop = "True"
    }
    if (PromoterStop %in% c("F", "FALSE", "False", FALSE)) {
        PromoterStop = "False"
    }
    if (NearestTwoDirection %in% c("T", "TRUE", "True", TRUE)) {
        NearestTwoDirection = "True"
    }
    if (NearestTwoDirection %in% c("F", "FALSE", "False", FALSE)) {
        NearestTwoDirection = "False"
    }
    if (UTR3 %in% c("T", "TRUE", "True", TRUE)) {
        UTR3 = "True"
    }
    if (UTR3 %in% c("F", "FALSE", "False", FALSE)) {
        UTR3 = "False"
    }
    if (adjacent %in% c("T", "TRUE", "True", TRUE)) {
        adjacent = "True"
    }
    if (adjacent %in% c("F", "FALSE", "False", FALSE)) {
        adjacent = "False"
    }
    if (adjacent == "True") {
        search_radius = 0
    }
    if (length(genome > 1)) 
        genome = genome[1]
    if (!collapsemethod %in% c("MaxMean", "function", "ME", "maxRowVariance", 
        "MinMean", "absMinMean", "absMaxMean", "Average")) {
        stop("please check the collapsemethod")
    }
    data(GO_BP_list, package = "seq2pathway.data")
    data(GO_MF_list, package = "seq2pathway.data")
    data(GO_CC_list, package = "seq2pathway.data")
    data(Des_BP_list, package = "seq2pathway.data")
    data(Des_CC_list, package = "seq2pathway.data")
    data(Des_MF_list, package = "seq2pathway.data")
    seq2gene_result <- runseq2gene(inputfile = inputfile, search_radius = search_radius, 
        promoter_radius = promoter_radius, promoter_radius2 = promoter_radius2, 
        genome = genome, adjacent = adjacent, SNP = SNP, PromoterStop = PromoterStop, 
        NearestTwoDirection = NearestTwoDirection, UTR3 = UTR3)
    seq2gene_result_fornext <- seq2gene_result[[2]]
    seq2gene_result_fornext <- seq2gene_result_fornext[, c(1, 
        13)]
    genename <- unique(seq2gene_result_fornext[, 2])
    print("Start test..............")
    if (FisherTest == TRUE) {
        if (DataBase %in% c("GOterm", "BP", "MF", "CC")) {
            FS_test <- FisherTest_GO_BP_MF_CC(gs = as.vector(genename), 
                genome = genome, min_Intersect_Count = min_Intersect_Count, 
                Ontology = DataBase)
        }
        else {
            FS_test <- FisherTest_MsigDB(gsmap = DataBase, gs = as.vector(genename), 
                genome = genome, min_Intersect_Count = min_Intersect_Count)
        }
    }
    if (FAIMETest == TRUE) {
        tmpinfile = tempfile()
        if (class(inputfile) == "data.frame") {
            if (ncol(inputfile) < 5) {
                stop("please check the format of the input data, some column is missing")
            }
            write.table(inputfile, file = tmpinfile, sep = "\t", 
                quote = FALSE, row.names = FALSE)
        }
        if (class(inputfile) == "GRanges") {
            test <- as.data.frame(inputfile)
            if (ncol(test) < 7) {
                stop("please check the format of the input data, some column is missing")
            }
            if (ncol(test) >= 7) {
                write.table(test[, c(6, 1, 2, 3, 7)], file = tmpinfile, 
                  sep = "\t", quote = FALSE, row.names = FALSE)
            }
        }
        peak_fornext <- read.table(file = tmpinfile, header = TRUE, 
            sep = "\t")
        if (ncol(peak_fornext) < 5) 
            stop("Please check input file format, some required column is missing.")
        peak_fornext <- peak_fornext[, c(1, 5)]
        peak_anno_score <- merge(seq2gene_result_fornext, peak_fornext, 
            by = names(seq2gene_result_fornext)[1], all = TRUE)
        dat_collapsed <- Peak_Gene_Collapse(input = peak_anno_score, 
            collapsemethod = collapsemethod)
        dat_CP <- data.frame(dat_collapsed[, c(2:ncol(dat_collapsed))])
        rownames(dat_CP) <- rownames(dat_collapsed)
        colnames(dat_CP) <- colnames(dat_collapsed)[2:ncol(dat_collapsed)]
        dat_collapsed$gene <- as.vector(toupper(rownames(dat_collapsed)))
        gene2pathway_result <- list()
        n.list = 0
        if (DataBase %in% c("GOterm", "BP", "CC", "MF")) {
            if (DataBase %in% c("GOterm", "BP")) {
                GO_BP_FAIME <- rungene2pathway(dat = dat_CP, 
                  gsmap = GO_BP_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", na.rm = na.rm)
                GO_BP_FAIME_N <- Normalize_F(input = GO_BP_FAIME)
                GO_BP_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
                  gsmap = GO_BP_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", B = B, na.rm = na.rm)
                GO_BP_N_P <- merge(GO_BP_FAIME_N, GO_BP_FAIME_Pvalue, 
                  by = "row.names", all = TRUE)
                rownames(GO_BP_N_P) <- GO_BP_N_P$Row.names
                GO_BP_N_P <- GO_BP_N_P[, -1]
                for (i in 1:nrow(GO_BP_N_P)) {
                  intsect <- intersect(toupper(rownames(dat_CP)), 
                    toupper(unlist(GO_BP_list[names(GO_BP_list) == 
                      rownames(GO_BP_N_P)[i]])))
                  GO_BP_N_P$Intersect_Count[i] <- length(intsect)
                  GO_BP_N_P$Intersect_gene[i] <- paste(intsect, 
                    collapse = " ")
                  GO_BP_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                    intsect, c(1)]), collapse = " ")
                  rm(intsect)
                  GO_BP_N_P$Des[i] <- as.character(Des_BP_list[which(names(Des_BP_list) == 
                    rownames(GO_BP_N_P)[i])])
                }
                GO_BP_N_P <- GO_BP_N_P[GO_BP_N_P$Intersect_Count >= 
                  min_Intersect_Count, ]
                GO_BP_N_P <- GO_BP_N_P[, c(ncol(GO_BP_N_P), 1:(ncol(GO_BP_N_P) - 
                  1))]
                n.list = n.list + 1
                gene2pathway_result[[n.list]] <- GO_BP_N_P
                names(gene2pathway_result)[n.list] <- c("GO_BP")
            }
            if (DataBase %in% c("GOterm", "MF")) {
                GO_MF_FAIME <- rungene2pathway(dat = dat_CP, 
                  gsmap = GO_MF_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", na.rm = na.rm)
                GO_MF_FAIME_N <- Normalize_F(input = GO_MF_FAIME)
                GO_MF_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
                  gsmap = GO_MF_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", B = B, na.rm = na.rm)
                GO_MF_N_P <- merge(GO_MF_FAIME_N, GO_MF_FAIME_Pvalue, 
                  by = "row.names", all = TRUE)
                rownames(GO_MF_N_P) <- GO_MF_N_P$Row.names
                GO_MF_N_P <- GO_MF_N_P[, -1]
                for (i in 1:nrow(GO_MF_N_P)) {
                  intsect <- intersect(toupper(rownames(dat_CP)), 
                    toupper(unlist(GO_MF_list[names(GO_MF_list) == 
                      rownames(GO_MF_N_P)[i]])))
                  GO_MF_N_P$Intersect_Count[i] <- length(intsect)
                  GO_MF_N_P$Intersect_gene[i] <- paste(intsect, 
                    collapse = " ")
                  GO_MF_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                    intsect, c(1)]), collapse = " ")
                  rm(intsect)
                  GO_MF_N_P$Des[i] <- as.character(Des_MF_list[which(names(Des_MF_list) == 
                    rownames(GO_MF_N_P)[i])])
                }
                GO_MF_N_P <- GO_MF_N_P[GO_MF_N_P$Intersect_Count >= 
                  min_Intersect_Count, ]
                GO_MF_N_P <- GO_MF_N_P[, c(ncol(GO_MF_N_P), 1:(ncol(GO_MF_N_P) - 
                  1))]
                n.list = n.list + 1
                gene2pathway_result[[n.list]] <- GO_MF_N_P
                names(gene2pathway_result)[n.list] <- c("GO_MF")
            }
            if (DataBase %in% c("GOterm", "CC")) {
                GO_CC_FAIME <- rungene2pathway(dat = dat_CP, 
                  gsmap = GO_CC_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", na.rm = na.rm)
                GO_CC_FAIME_N <- Normalize_F(input = GO_CC_FAIME)
                GO_CC_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
                  gsmap = GO_CC_list, alpha = alpha, logCheck = logCheck, 
                  method = "FAIME", B = B, na.rm = na.rm)
                GO_CC_N_P <- merge(GO_CC_FAIME_N, GO_CC_FAIME_Pvalue, 
                  by = "row.names", all = TRUE)
                rownames(GO_CC_N_P) <- GO_CC_N_P$Row.names
                GO_CC_N_P <- GO_CC_N_P[, -1]
                for (i in 1:nrow(GO_CC_N_P)) {
                  intsect <- intersect(toupper(rownames(dat_CP)), 
                    toupper(unlist(GO_CC_list[names(GO_CC_list) == 
                      rownames(GO_CC_N_P)[i]])))
                  GO_CC_N_P$Intersect_Count[i] <- length(intsect)
                  GO_CC_N_P$Intersect_gene[i] <- paste(intsect, 
                    collapse = " ")
                  GO_CC_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                    intsect, c(1)]), collapse = " ")
                  rm(intsect)
                  GO_CC_N_P$Des[i] <- as.character(Des_CC_list[which(names(Des_CC_list) == 
                    rownames(GO_CC_N_P)[i])])
                }
                GO_CC_N_P <- GO_CC_N_P[GO_CC_N_P$Intersect_Count >= 
                  min_Intersect_Count, ]
                GO_CC_N_P <- GO_CC_N_P[, c(ncol(GO_CC_N_P), 1:(ncol(GO_CC_N_P) - 
                  1))]
                n.list = n.list + 1
                gene2pathway_result[[n.list]] <- GO_CC_N_P
                names(gene2pathway_result)[n.list] <- c("GO_CC")
            }
        }
        else {
            dat_FAIME <- rungene2pathway(dat = dat_CP, gsmap = DataBase, 
                alpha = alpha, logCheck = logCheck, method = "FAIME", 
                na.rm = na.rm)
            N_FAIME <- Normalize_F(input = dat_FAIME)
            dat_FAIME_Pvalue <- rungene2pathway_EmpiricalP(dat = dat_CP, 
                gsmap = DataBase, alpha = alpha, logCheck = logCheck, 
                method = "FAIME", B = B, na.rm = na.rm)
            N_FAIME <- as.matrix(N_FAIME)
            dat_FAIME_Pvalue <- as.matrix(dat_FAIME_Pvalue)
            DB_N_P <- cbind(N_FAIME, as.matrix(dat_FAIME_Pvalue[match(rownames(N_FAIME), 
                rownames(dat_FAIME_Pvalue)), ]))
            colnames(DB_N_P) <- c("score2pathscore_Normalized", 
                "score2pathscore_Pvalue")
            DB_N_P <- as.data.frame(DB_N_P)
            for (i in 1:nrow(DB_N_P)) {
                if (class(DataBase) == "GSA.genesets") {
                  intsect <- intersect(toupper(rownames(dat_CP)), 
                    toupper(unlist(DataBase$genesets[which(DataBase$geneset.names == 
                      rownames(DB_N_P)[i])])))
                }
                else if (class(DataBase) == "list") {
                  intsect <- intersect(toupper(rownames(dat_CP)), 
                    toupper(unlist(DataBase[names(DataBase) == 
                      rownames(DB_N_P)[i]])))
                }
                DB_N_P$Intersect_Count[i] <- length(intsect)
                DB_N_P$Intersect_gene[i] <- paste(intsect, collapse = " ")
                DB_N_P$Intersect_element[i] <- paste(as.vector(dat_collapsed[dat_collapsed$gene %in% 
                  intsect, c(1)]), collapse = " ")
                rm(intsect)
                if (class(DataBase) == "GSA.genesets") {
                  DB_N_P$Des[i] <- as.character(DataBase$geneset.descriptions[which(DataBase$geneset.names == 
                    rownames(DB_N_P)[i])])
                }
            }
            DB_N_P <- DB_N_P[DB_N_P$Intersect_Count >= min_Intersect_Count, 
                ]
            gene2pathway_result <- DB_N_P[, c(ncol(DB_N_P), 1:(ncol(DB_N_P) - 
                1))]
        }
        print("gene2pathway analysis is done")
    }
    if (exists("gene2pathway_result") & exists("FS_test")) {
        TotalResult <- list()
        TotalResult[[1]] <- seq2gene_result
        names(TotalResult)[1] <- "seq2gene_result"
        TotalResult[[2]] <- gene2pathway_result
        names(TotalResult)[2] <- "gene2pathway_result.FAIME"
        TotalResult[[3]] <- FS_test
        names(TotalResult)[3] <- "gene2pathway_result.FET"
        TotalResult[[4]] <- dat_CP
        names(TotalResult)[4] <- "gene_collapse"
    }
    else if (exists("gene2pathway_result") & exists("FS_test") == 
        FALSE) {
        TotalResult <- list()
        TotalResult[[1]] <- seq2gene_result
        names(TotalResult)[1] <- "seq2gene_result"
        TotalResult[[2]] <- gene2pathway_result
        names(TotalResult)[2] <- "gene2pathway_result.FAIME"
        TotalResult[[3]] <- dat_CP
        names(TotalResult)[3] <- "gene_collapse"
    }
    else if (exists("gene2pathway_result") == FALSE & exists("FS_test")) {
        TotalResult <- list()
        TotalResult[[1]] <- seq2gene_result
        names(TotalResult)[1] <- "seq2gene_result"
        TotalResult[[2]] <- FS_test
        names(TotalResult)[2] <- "gene2pathway_result.FET"
    }
    return(TotalResult)
}
<bytecode: 0x7f973ecbddd0>
<environment: namespace:seq2pathway>
 --- function search by body ---
Function runseq2pathway in namespace seq2pathway has this body.
 ----------- END OF FAILURE REPORT -------------- 
Fatal error: the condition has length > 1
* 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, 2 WARNINGs, 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.9-bioc/meat/seq2pathway.Rcheck/00check.log’
for details.


Installation output

seq2pathway.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL seq2pathway
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/3.6/Resources/library’
* installing *source* package ‘seq2pathway’ ...
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (seq2pathway)

Tests output


Example timings

seq2pathway.Rcheck/seq2pathway-Ex.timings

nameusersystemelapsed
Chipseq_Peak_demo0.0260.0010.028
FisherTest_GO_BP_MF_CC4.2690.2384.532
FisherTest_MsigDB2.5910.1362.744
GRanges_demo0.0020.0010.003
addDescription0.3260.0227.017
dat_RNA0.0140.0040.019
dat_chip0.0020.0000.003
gene2pathway_test0.9820.0541.046
plotTop104.2790.2544.560
runseq2gene47.242 1.71249.472