I have performed gene set analysis (GSA) using gsameth from missMethyl package for EPICv2 array. I noticed that the probes annotated to more than one gene gets completely excluded from the analysis. I found the reason and corrected it but was curios if it is isolated case. The problem lies in one of the subfunctions of gsameth.

In gsameth => getMappedEntrezIDs => .getFlatAnnotation

# This is the way i tested it
Anno <- getAnnotation(IlluminaHumanMethylationEPICv2anno.20a1.hg38)
flat_test <- .getFlatAnnotation(array.type = "EPIC_V2", anno = Anno) 
> head(rownames(flat_test))
[1] "cg25324105_BC111" "cg25383568_TC111" "cg25623721_TC111" "cg25898577_BC11"  "cg25908985_BC11"  "cg25910443_TC111"

# And this is the line where the problem is located within the .getFlatAnnotation
flat <- data.frame(symbol = unlist(geneslist), group = unlist(grouplist))

This results in inaccurate transformation of list into dataframe for probes with multiple genes. Probes change from cg25324105_BC11 to cg25324105_BC111

Then I decided to change it to

  flat <- data.frame(
    rowname = rep(names(geneslist), lengths(geneslist)), 
    symbol = unlist(geneslist), 
    group = unlist(grouplist))

> head(flat$rowname)
[1] "cg00381604_BC11" "cg00381604_BC11" "cg00381604_BC11" "cg00381604_BC11" "cg00381604_BC11" "cg21870274_BC21"
# And in subsequent lines I changed rownames(flat) to flat$rowname

# sessionInfo( )
R Under development (unstable) (2024-12-20 r87452 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)

Matrix products: default


attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] tibble_3.2.1                                        ggplot2_3.5.1                                      
 [3] stringr_1.5.1                                       rtracklayer_1.67.0                                 
 [5] org.Hs.eg.db_3.20.0                                 AnnotationDbi_1.69.0                               
 [7] qusage_2.41.0                                       missMethyl_1.41.0                                  
 [9] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0 IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.1 
[11] DMRcatedata_2.25.0                                  ExperimentHub_2.15.0                               
[13] AnnotationHub_3.15.0                                BiocFileCache_2.15.0                               
[15] dbplyr_2.5.0                                        DMRcate_3.3.1                                      
[17] limma_3.63.2                                        readxl_1.4.3                                       
[19] readr_2.1.5                                         dplyr_1.1.4                                        
[21] data.table_1.16.4                                   IlluminaHumanMethylationEPICv2anno.20a1.hg38_1.0.0 
[23] IlluminaHumanMethylationEPICv2manifest_1.0.0        minfi_1.53.1                                       
[25] bumphunter_1.49.0                                   locfit_1.5-9.10                                    
[27] iterators_1.0.14                                    foreach_1.5.2                                      
[29] Biostrings_2.75.3                                   XVector_0.47.0                                     
[31] SummarizedExperiment_1.37.0                         Biobase_2.67.0                                     
[33] MatrixGenerics_1.19.0                               matrixStats_1.4.1                                  
[35] GenomicRanges_1.59.1                                GenomeInfoDb_1.43.2                                
[37] IRanges_2.41.2                                      S4Vectors_0.45.2                                   
[39] BiocGenerics_0.53.3                                 generics_0.1.3                                     

loaded via a namespace (and not attached):
  [1] ProtGenerics_1.39.1       bitops_1.0-9              httr_1.4.7                RColorBrewer_1.1-3        tools_4.5.0              
  [6] doRNG_1.8.6               backports_1.5.0           R6_2.5.1                  HDF5Array_1.35.2          lazyeval_0.2.2           
 [11] Gviz_1.51.0               rhdf5filters_1.19.0       permute_0.9-7             withr_3.0.2               prettyunits_1.2.0        
 [16] gridExtra_2.3             base64_2.0.2              preprocessCore_1.69.0     cli_3.6.3                 labeling_0.4.3           
 [21] mvtnorm_1.3-2             genefilter_1.89.0         tidytable_0.11.2          askpass_1.2.1             Rsamtools_2.23.1         
 [26] foreign_0.8-87            siggenes_1.81.0           illuminaio_0.49.0         R.utils_2.12.3            rentrez_1.2.3            
 [31] dichromat_2.0-0.1         scrime_1.3.5              BSgenome_1.75.0           rstudioapi_0.17.1         RSQLite_2.3.9            
 [36] BiocIO_1.17.1             gtools_3.9.5              Matrix_1.7-1              interp_1.1-6              abind_1.4-8              
 [41] R.methodsS3_1.8.2         lifecycle_1.0.4           yaml_2.3.10               edgeR_4.5.1               rhdf5_2.51.1             
 [46] SparseArray_1.7.2         grid_4.5.0                blob_1.2.4                crayon_1.5.3              lattice_0.22-6           
 [51] beachmat_2.23.5           GenomicFeatures_1.59.1    annotate_1.85.0           KEGGREST_1.47.0           pillar_1.10.0            
 [56] knitr_1.49                beanplot_1.3.1            rjson_0.2.23              fftw_1.0-9                estimability_1.5.1       
 [61] codetools_0.2-20          glue_1.8.0                remotes_2.5.0             vctrs_0.6.5               png_0.1-8                
 [66] cellranger_1.1.0          gtable_0.3.6              cachem_1.1.0              xfun_0.49                 S4Arrays_1.7.1           
 [71] mime_0.12                 survival_3.8-3            statmod_1.5.0             nlme_3.1-166              bit64_4.5.2              
 [76] bsseq_1.43.1              progress_1.2.3            filelock_1.0.3            nor1mix_1.3-3             rpart_4.1.23             
 [81] colorspace_2.1-1          DBI_1.2.3                 Hmisc_5.2-1               nnet_7.3-19               tidyselect_1.2.1         
 [86] emmeans_1.10.6            bit_4.5.0.1               compiler_4.5.0            curl_6.0.1                httr2_1.0.7              
 [91] htmlTable_2.4.3           BiasedUrn_2.0.12          xml2_1.3.6                DelayedArray_0.33.3       checkmate_2.3.2          
 [96] scales_1.3.0              quadprog_1.5-8            rappdirs_0.3.3            digest_0.6.37             rmarkdown_2.29           
[101] GEOquery_2.75.0           htmltools_0.5.8.1         pkgconfig_2.0.3           jpeg_0.1-10               base64enc_0.1-3          
[106] sparseMatrixStats_1.19.0  fastmap_1.2.0             ensembldb_2.31.0          rlang_1.1.4               htmlwidgets_1.6.4        
[111] UCSC.utils_1.3.0          DelayedMatrixStats_1.29.0 farver_2.1.2              jsonlite_1.8.9            BiocParallel_1.41.0      
[116] mclust_6.1.1              R.oo_1.27.0               VariantAnnotation_1.53.0  RCurl_1.98-1.16           magrittr_2.0.3           
[121] Formula_1.2-5             GenomeInfoDbData_1.2.13   Rhdf5lib_1.29.0           munsell_0.5.1             Rcpp_1.0.13-1            
[126] stringi_1.8.4             zlibbioc_1.53.0           MASS_7.3-61               plyr_1.8.9                deldir_2.0-4             
[131] splines_4.5.0             multtest_2.63.0           hms_1.1.3                 rngtools_1.5.2            biomaRt_2.63.0           
[136] BiocVersion_3.21.1        XML_3.99-0.17             evaluate_1.0.1            latticeExtra_0.6-30       biovizBase_1.55.0        
[141] BiocManager_1.30.25       tzdb_0.4.0                tidyr_1.3.1               openssl_2.3.0             purrr_1.0.2              
[146] reshape_0.8.9             xtable_1.8-4              restfulr_0.0.15           AnnotationFilter_1.31.0   memoise_2.0.1            
[151] GenomicAlignments_1.43.0  cluster_2.1.8