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### Running command:
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###   /home/biocbuild/R/R-4.3.1/bin/R CMD check --install=check:EGSEA.install-out.txt --library=/home/biocbuild/R/R-4.3.1/site-library --no-vignettes --timings EGSEA_1.30.0.tar.gz
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* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/EGSEA.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘EGSEA/DESCRIPTION’ ... OK
* this is package ‘EGSEA’ version ‘1.30.0’
* 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 ‘EGSEA’ 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 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
buildGeneSetDBIdx: no visible binding for global variable ‘GOTERM’
buildMSigDBIdx: no visible binding for global variable ‘msigdb’
generateSummaryPlots: no visible binding for global variable ‘x.data’
generateSummaryPlots: no visible binding for global variable ‘y.data’
generateSummaryPlots: no visible binding for global variable ‘gsSize’
generateSummaryPlots: no visible binding for global variable ‘id’
generateSummaryPlots: no visible binding for global variable ‘sig’
loadKeggData: no visible binding for global variable ‘kegg.pathways’
Undefined global functions or variables:
  GOTERM gsSize id kegg.pathways msigdb sig x.data y.data
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... WARNING
Undocumented data sets:
  ‘arraydata’
All user-level objects in a package should have documentation entries.
See chapter ‘Writing R documentation files’ in the ‘Writing R
Extensions’ manual.
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... WARNING
'library' or 'require' call not declared from: ‘Glimma’
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘EGSEA-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: EGSEAResults
> ### Title: The EGSEAResults class
> ### Aliases: EGSEAResults EGSEAResults-class $,EGSEAResults-method topSets
> ###   topSets,EGSEAResults-method show,EGSEAResults-method
> ###   summary,EGSEAResults-method limmaTopTable
> ###   limmaTopTable,EGSEAResults-method generateReport
> ###   generateReport,EGSEAResults-method getlimmaResults
> ###   getlimmaResults,EGSEAResults-method plotHeatmap
> ###   plotHeatmap,EGSEAResults-method plotSummaryHeatmap
> ###   plotSummaryHeatmap,EGSEAResults-method plotPathway
> ###   plotPathway,EGSEAResults-method plotMethods
> ###   plotMethods,EGSEAResults-method plotSummary
> ###   plotSummary,EGSEAResults-method plotGOGraph
> ###   plotGOGraph,EGSEAResults-method plotBars plotBars,EGSEAResults-method
> ###   showSetByName showSetByName,EGSEAResults-method showSetByID
> ###   showSetByID,EGSEAResults-method getSetScores
> ###   getSetScores,EGSEAResults-method
> 
> ### ** Examples
> 
> # Exampple of EGSEAResults
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> print(gsa$baseMethods)
 [1] "camera"     "safe"       "gage"       "padog"      "plage"     
 [6] "zscore"     "gsva"       "ssgsea"     "globaltest" "ora"       
> 
> # Example of topSets
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> topSets(gsa,  gs.label="kegg",contrast=1, number = 10)
Extracting the top gene sets of the collection 
KEGG Pathways for the contrast X24IL13-X24
 Sorted by avg.rank
 [1] "Amoebiasis"                                               
 [2] "Asthma"                                                   
 [3] "Intestinal immune network for IgA production"             
 [4] "Endocrine and other factor-regulated calcium reabsorption"
 [5] "Viral myocarditis"                                        
 [6] "HTLV-I infection"                                         
 [7] "Prion diseases"                                           
 [8] "Proteoglycans in cancer"                                  
 [9] "Hematopoietic cell lineage"                               
[10] "Legionellosis"                                            
> topSets(gsa,  gs.label=1, contrast=1, sort.by="ora", number = 10, 
+ names.only=FALSE)
Extracting the top gene sets of the collection 
c2 Curated Gene Sets for the contrast X24IL13-X24
 Sorted by ora
                                               Rank      p.value        p.adj
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN       1 2.084798e-49 3.901699e-46
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP    2 5.752312e-28 1.957355e-25
NABA_MATRISOME                                    3 2.503133e-24 4.461536e-22
RUTELLA_RESPONSE_TO_HGF_UP                        4 7.905113e-33 4.931473e-30
NABA_MATRISOME_ASSOCIATED                         5 2.007033e-61 7.512324e-58
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN        6 6.058174e-37 5.668936e-34
MCLACHLAN_DENTAL_CARIES_UP                        7 4.443436e-34 3.326356e-31
LENAOUR_DENDRITIC_CELL_MATURATION_UP              8 2.413176e-43 3.010840e-40
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP      9 1.818059e-29 7.561105e-27
ONDER_CDH1_TARGETS_2_DN                          10 7.407783e-31 3.961047e-28
                                               vote.rank avg.rank med.rank
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN            5   1573.9   1061.5
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP       355    815.8    403.5
NABA_MATRISOME                                         5   1666.3   1495.0
RUTELLA_RESPONSE_TO_HGF_UP                          3210   1519.6   1242.5
NABA_MATRISOME_ASSOCIATED                              5   1292.7   1117.5
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN            10   1414.5   1343.5
MCLACHLAN_DENTAL_CARIES_UP                            10   1509.0   1626.0
LENAOUR_DENDRITIC_CELL_MATURATION_UP                  20    224.8     69.5
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP          10    817.3    695.5
ONDER_CDH1_TARGETS_2_DN                               10   1420.6   1561.0
                                                 min.pvalue min.rank avg.logfc
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN    6.105360e-32        1  2.479176
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP 6.316000e-28        2  1.733495
NABA_MATRISOME                                 1.924738e-27        3  2.367135
RUTELLA_RESPONSE_TO_HGF_UP                     4.873555e-27        4  1.743617
NABA_MATRISOME_ASSOCIATED                      1.486914e-42        1  2.425162
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN     8.472735e-26        4  1.894696
MCLACHLAN_DENTAL_CARIES_UP                     4.952318e-25        7  1.517220
LENAOUR_DENDRITIC_CELL_MATURATION_UP           2.474903e-21        8  2.483170
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP   1.277895e-20        9  1.535780
ONDER_CDH1_TARGETS_2_DN                        2.310221e-19        6  1.578958
                                               avg.logfc.dir direction
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN         2.832590        Up
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP      1.924505        Up
NABA_MATRISOME                                      2.669640        Up
RUTELLA_RESPONSE_TO_HGF_UP                         -1.687618      Down
NABA_MATRISOME_ASSOCIATED                           2.816744        Up
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN          1.881403        Up
MCLACHLAN_DENTAL_CARIES_UP                         -1.380719      Down
LENAOUR_DENDRITIC_CELL_MATURATION_UP                2.518874        Up
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP       -1.639309      Down
ONDER_CDH1_TARGETS_2_DN                            -1.465519      Down
                                               significance camera safe gage
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN        81.26167   2822  891    2
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP     30.91754    353  702 3389
NABA_MATRISOME                                     36.48130   1131  704 3743
RUTELLA_RESPONSE_TO_HGF_UP                         36.88600   3206  731   21
NABA_MATRISOME_ASSOCIATED                         100.00000   1508  727    1
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN         45.46993   1856  831    7
MCLACHLAN_DENTAL_CARIES_UP                         33.37908   1157  797    9
LENAOUR_DENDRITIC_CELL_MATURATION_UP               70.83970     17  917   18
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP       28.95774    263  732   33
ONDER_CDH1_TARGETS_2_DN                            31.23164   1671 1451    6
                                               padog plage zscore gsva ssgsea
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN        2  3310   3676 3536   1232
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP   192  1161    441 1435    366
NABA_MATRISOME                                     3  3161   1859 2109   3426
RUTELLA_RESPONSE_TO_HGF_UP                       195  1754   2679 3227   3035
NABA_MATRISOME_ASSOCIATED                          1  2680   2220 2350   3007
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN         4  2970   2005 2494   3497
MCLACHLAN_DENTAL_CARIES_UP                       200  3031   2777 2796   2095
LENAOUR_DENDRITIC_CELL_MATURATION_UP             193   756     17  183     28
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP      10  1811   1769 1598   1289
ONDER_CDH1_TARGETS_2_DN                            8  2245   2448 2736   2931
                                               globaltest ora
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_10D_DN           267   1
FULCHER_INFLAMMATORY_RESPONSE_LECTIN_VS_LPS_UP        117   2
NABA_MATRISOME                                        524   3
RUTELLA_RESPONSE_TO_HGF_UP                            344   4
NABA_MATRISOME_ASSOCIATED                             428   5
TAKEDA_TARGETS_OF_NUP98_HOXA9_FUSION_8D_DN            475   6
MCLACHLAN_DENTAL_CARIES_UP                           2221   7
LENAOUR_DENDRITIC_CELL_MATURATION_UP                  111   8
RUTELLA_RESPONSE_TO_HGF_VS_CSF2RB_AND_IL4_UP          659   9
ONDER_CDH1_TARGETS_2_DN                               700  10
> topSets(gsa,  gs.label="kegg",contrast=0, number = 10)
Extracting the top gene sets of the collection 
KEGG Pathways for the contrast comparison
 Sorted by avg.rank
 [1] "Asthma"                                      
 [2] "Viral myocarditis"                           
 [3] "Intestinal immune network for IgA production"
 [4] "Amoebiasis"                                  
 [5] "HTLV-I infection"                            
 [6] "NOD-like receptor signaling pathway"         
 [7] "Hematopoietic cell lineage"                  
 [8] "Malaria"                                     
 [9] "Legionellosis"                               
[10] "Toll-like receptor signaling pathway"        
> 
> # Example of show
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> show(gsa)
An object of class "EGSEAResults"
	Total number of genes: 17343
	Total number of samples: 8
	Contrasts: X24IL13-X24, X24IL13Ant-X24IL13
	Base GSE methods: camera (limma:3.31.10), safe (safe:3.15.0), gage (gage:2.25.0), padog (PADOG:1.17.0), plage (GSVA:1.23.3), zscore (GSVA:1.23.3), gsva (GSVA:1.23.3), ssgsea (GSVA:1.23.3), globaltest (globaltest:5.29.1), ora (stats:3.4.0)
	P-values combining method: fisher
	Sorting statistic: avg.rank
	Organism: Homo sapiens
	HTML report generated: Yes
	HTML report directory: ./il13-egsea-report
	Tested gene set collections: 
		c2 Curated Gene Sets (c2): 3747 gene sets - Version: 5.2, Update date: 07 March 2017
		c5 GO Gene Sets (c5): 6166 gene sets - Version: 5.2, Update date: 07 March 2017
		KEGG Pathways (kegg): 203 gene sets - Version: NA, Update date: 07 March 2017
	EGSEA version: 1.3.1
	EGSEAdata version: 1.3.1
Use summary(object) and topSets(object, ...) to explore this object.
> 
> # Example of summary
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> summary(gsa)
**** Top 10 gene sets in the c2 Curated Gene Sets collection **** 
** Contrast X24IL13-X24 **
LU_IL4_SIGNALING | LIEN_BREAST_CARCINOMA_METAPLASTIC_VS_DUCTAL_UP
LINDSTEDT_DENDRITIC_CELL_MATURATION_D | LENAOUR_DENDRITIC_CELL_MATURATION_UP
REACTOME_PD1_SIGNALING | SCHOEN_NFKB_SIGNALING
PID_NOTCH_PATHWAY | PID_INTEGRIN_A9B1_PATHWAY
MAHADEVAN_IMATINIB_RESISTANCE_UP | LUI_THYROID_CANCER_CLUSTER_4

** Contrast X24IL13Ant-X24IL13 **
SCHOEN_NFKB_SIGNALING | GRAHAM_CML_QUIESCENT_VS_CML_DIVIDING_UP
MAHADEVAN_IMATINIB_RESISTANCE_UP | DAZARD_UV_RESPONSE_CLUSTER_G28
HAHTOLA_MYCOSIS_FUNGOIDES_CD4_UP | LU_IL4_SIGNALING
TIAN_TNF_SIGNALING_VIA_NFKB | ZHAN_MULTIPLE_MYELOMA_DN
LIANG_SILENCED_BY_METHYLATION_2 | REACTOME_PD1_SIGNALING

** Comparison analysis ** 
SCHOEN_NFKB_SIGNALING | LU_IL4_SIGNALING
MAHADEVAN_IMATINIB_RESISTANCE_UP | REACTOME_PD1_SIGNALING
LIEN_BREAST_CARCINOMA_METAPLASTIC_VS_DUCTAL_UP | LENAOUR_DENDRITIC_CELL_MATURATION_UP
LUI_THYROID_CANCER_CLUSTER_4 | LINDSTEDT_DENDRITIC_CELL_MATURATION_D
IIZUKA_LIVER_CANCER_EARLY_RECURRENCE | WU_HBX_TARGETS_3_DN

**** Top 10 gene sets in the c5 GO Gene Sets collection **** 
** Contrast X24IL13-X24 **
GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE_MEMBRANE | GO_CLATHRIN_COATED_VESICLE_MEMBRANE
GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE | GO_ICOSANOID_BIOSYNTHETIC_PROCESS
GO_FATTY_ACID_DERIVATIVE_BIOSYNTHETIC_PROCESS | GO_UNSATURATED_FATTY_ACID_BIOSYNTHETIC_PROCESS
GO_POSITIVE_REGULATION_OF_CYTOKINE_SECRETION | GO_MHC_CLASS_II_PROTEIN_COMPLEX
GO_MHC_CLASS_II_RECEPTOR_ACTIVITY | GO_LEUKOTRIENE_METABOLIC_PROCESS

** Contrast X24IL13Ant-X24IL13 **
GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE_MEMBRANE | GO_POSITIVE_REGULATION_OF_NF_KAPPAB_IMPORT_INTO_NUCLEUS
GO_MHC_CLASS_II_PROTEIN_COMPLEX | GO_CLATHRIN_COATED_VESICLE_MEMBRANE
GO_IGG_BINDING | GO_POSITIVE_REGULATION_OF_ACUTE_INFLAMMATORY_RESPONSE
GO_CXCR_CHEMOKINE_RECEPTOR_BINDING | GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE
GO_POSITIVE_REGULATION_OF_INTERLEUKIN_1_SECRETION | GO_MHC_CLASS_II_RECEPTOR_ACTIVITY

** Comparison analysis ** 
GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE_MEMBRANE | GO_CLATHRIN_COATED_VESICLE_MEMBRANE
GO_CLATHRIN_COATED_ENDOCYTIC_VESICLE | GO_MHC_CLASS_II_PROTEIN_COMPLEX
GO_POSITIVE_REGULATION_OF_NF_KAPPAB_IMPORT_INTO_NUCLEUS | GO_MHC_CLASS_II_RECEPTOR_ACTIVITY
GO_POSITIVE_REGULATION_OF_CYTOKINE_SECRETION | GO_POSITIVE_REGULATION_OF_ACUTE_INFLAMMATORY_RESPONSE
GO_IGG_BINDING | GO_ANTIGEN_BINDING

**** Top 10 gene sets in the KEGG Pathways collection **** 
** Contrast X24IL13-X24 **
Amoebiasis | Asthma
Intestinal immune network for IgA production | Endocrine and other factor-regulated calcium reabsorption
Viral myocarditis | HTLV-I infection
Prion diseases | Proteoglycans in cancer
Hematopoietic cell lineage | Legionellosis

** Contrast X24IL13Ant-X24IL13 **
Malaria | Viral myocarditis
NOD-like receptor signaling pathway | Toll-like receptor signaling pathway
Asthma | Legionellosis
Hematopoietic cell lineage | Rheumatoid arthritis
HTLV-I infection | Melanoma

** Comparison analysis ** 
Asthma | Viral myocarditis
Intestinal immune network for IgA production | Amoebiasis
HTLV-I infection | NOD-like receptor signaling pathway
Hematopoietic cell lineage | Malaria
Legionellosis | Toll-like receptor signaling pathway

> 
> # Example of limmaTopTable
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> colnames(limmaTopTable(gsa))
[1] "FeatureID" "Symbols"   "logFC"     "AveExpr"   "t"         "P.Value"  
[7] "adj.P.Val" "B"        
> head(limmaTopTable(gsa))
      FeatureID Symbols     logFC  AveExpr         t      P.Value    adj.P.Val
2208       2208   FCER2  5.818129 3.356316  24.97210 2.328014e-10 2.018738e-06
30835     30835   CD209  3.882492 4.818066  25.93935 1.598970e-10 2.018738e-06
2675       2675   GFRA2  3.277526 3.319754  22.93290 5.395423e-10 2.339320e-06
3554       3554   IL1R1  2.303161 5.728493  22.98881 5.267500e-10 2.339320e-06
55022     55022    PID1 -3.454681 4.012016 -21.56122 9.900617e-10 3.434128e-06
7850       7850   IL1R2  3.336171 4.158437  20.19777 1.880207e-09 5.434739e-06
             B
2208  13.25669
30835 14.52844
2675  13.13380
3554  13.62705
55022 12.71054
7850  12.26003
> 
> # Example of generateReport
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> # generateReport(gsa)
> 
> # Example of getlimmaResults
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> fit = getlimmaResults(gsa)
> class(fit)
[1] "MArrayLM"
attr(,"package")
[1] "limma"
> names(fit)
 [1] "coefficients"     "stdev.unscaled"   "sigma"            "df.residual"     
 [5] "cov.coefficients" "rank"             "genes"            "Amean"           
 [9] "method"           "design"           "contrasts"        "df.prior"        
[13] "s2.prior"         "var.prior"        "proportion"       "s2.post"         
[17] "t"                "df.total"         "p.value"          "lods"            
[21] "F"                "F.p.value"       
> 
> # Example of plotHeatmap
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotHeatmap(gsa, "Asthma", gs.label="kegg")
Generating heatmap for Asthma from the collection 
KEGG Pathways and for the contrast X24IL13-X24
> plotHeatmap(gsa, "Asthma", gs.label="kegg", contrast = "comparison", 
+ file.name = "asthma.hm.cmp")
Generating heatmap for Asthma from the collection 
KEGG Pathways and for the contrast comparison
> 
> # Example of plotSummaryHeatmap
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotSummaryHeatmap(gsa, gs.label="kegg")
Generating summary heatmap for the collection KEGG Pathways
sort.by: avg.rank, hm.vals: avg.rank, show.vals: 
> 
> # Example of plotPathway
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotPathway(gsa, gs.label="kegg", "Asthma")
Generating pathway map for Asthma from the collection 
KEGG Pathways and for the contrast X24IL13-X24
[1] TRUE
> plotPathway(gsa, gs.label="kegg", "Asthma", contrast="comparison", 
+ file.name = "asthma.map.cmp")
Generating pathway map for Asthma from the collection 
KEGG Pathways and for the contrast comparison
[1] TRUE
> 
> # Example of plotMethods
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotMethods(gsa)
Generating methods plot for the collection 
c2 Curated Gene Sets and for the contrast X24IL13-X24
character(0)
> 
> # Example of plotSummary
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotSummary(gsa)
Generating Summary plots for the collection 
c2 Curated Gene Sets and for the contrast X24IL13-X24
> plotSummary(gsa, contrast=c(1,2), file.name = "summary.cmp")
Generating Summary plots for the collection 
c2 Curated Gene Sets and for the comparison X24IL13-X24 vs X24IL13Ant-X24IL13
> 
> # Example of plotGOGraph
> library(EGSEAdata)
> data(il13.gsa)
> gsa = il13.gsa
> class(gsa)
[1] "EGSEAResults"
attr(,"package")
[1] "EGSEA"
> plotGOGraph(gsa, sort.by="avg.rank")
Generating GO Graphs for the collection c5 GO Gene Sets
 and for the contrast X24IL13-X24 based on the avg.rank

Building most specific GOs .....
Loading required package: org.Hs.eg.db
	( 11140 GO terms found. )

Build GO DAG topology ..........
	( 14547 GO terms and 32701 relations. )

Annotating nodes ...............
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 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, 2 WARNINGs, 1 NOTE
See
  ‘/home/biocbuild/bbs-3.18-bioc/meat/EGSEA.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.1/bin/R CMD INSTALL EGSEA
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.3.1/site-library’
* installing *source* package ‘EGSEA’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading

groupGOTerms: 	GOBPTerm, GOMFTerm, GOCCTerm environments built.
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location

groupGOTerms: 	GOBPTerm, GOMFTerm, GOCCTerm environments built.
** testing if installed package can be loaded from final location

groupGOTerms: 	GOBPTerm, GOMFTerm, GOCCTerm environments built.
** testing if installed package keeps a record of temporary installation path
* DONE (EGSEA)

R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(EGSEA)
Loading required package: Biobase
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

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, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: gage

Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: topGO
Loading required package: graph
Loading required package: GO.db
Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve


groupGOTerms: 	GOBPTerm, GOMFTerm, GOCCTerm environments built.

Attaching package: 'topGO'

The following object is masked from 'package:IRanges':

    members

The following object is masked from 'package:gage':

    geneData

Loading required package: pathview

##############################################################################
Pathview is an open source software package distributed under GNU General
Public License version 3 (GPLv3). Details of GPLv3 is available at
http://www.gnu.org/licenses/gpl-3.0.html. Particullary, users are required to
formally cite the original Pathview paper (not just mention it) in publications
or products. For details, do citation("pathview") within R.

The pathview downloads and uses KEGG data. Non-academic uses may require a KEGG
license agreement (details at http://www.kegg.jp/kegg/legal.html).
##############################################################################




> 
> test_check("EGSEA")
[1] "Created the User-Defined Gene Sets collection ... "
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 8 ]
> 
> proc.time()
   user  system elapsed 
 21.090   2.167  26.001