Hello everyone,

Back in October I performed fgsea analysis without problem, obtaining up/downregulated genesets. Now I am trying to do another analysis with fgsea, and I keep getting the same error, which I am unable to resolve. The error is:

"Error in names(res) <- *vtmp* : 'names' attribute [30] must be the same length as the vector [20]"

I have already checked a thousand times whether my ranked genelist has correct, non duplicated, non-missing names, which definitly is the case. Also have I tried multiple ways of importing the Hallmark genesets (first through msigdbr package in R en later by downloading the .gmt file), both which are not working. Furthermore, have I tried to update all packages, upgrading R to the newest version and also running my analysis of October again, which yielded me the same error.

Are other people also experiencing this error and if so, did you find a workaround? Any advice is greatly appreciated.

See below my code used and version number of R and related packages:

 #GSEA
    GSEA_ranks <- TT[,c(4,5,8)]
    GSEA_ranks$metric <- -log10(GSEA_ranks$PValue)/sign(GSEA_ranks$logFC)
    GSEA_ranks$SYMBOL <- GSEA_ranks$hgnc_symbol
    GSEA_ranks1 <- subset(GSEA_ranks, select = c("SYMBOL", "metric"))
    GSEA_ranks1 <- as.data.frame(GSEA_ranks1)

    GSEA_ranks2 <- GSEA_ranks1 %>% 
      select(SYMBOL, metric) %>% 
      na.omit() %>% 
      distinct() %>% 
      group_by(SYMBOL) %>% 
      summarize(metric=mean(metric))

    table(duplicated(GSEA_ranks2$SYMBOL))
    table(is.na(GSEA_ranks2$SYMBOL))
    summary(GSEA_ranks2$metric)

    #ordering the result
    GSEA_ranks2 <- GSEA_ranks2[order(GSEA_ranks2$metric, decreasing = T),]

    #creating ranked gene list
    ranks <- GSEA_ranks2$metric
    names(ranks) <- GSEA_ranks2$SYMBOL

    msig <- msigdbr(species = "human", category = "H")
    msigdbr_list <-  split(x = msig$gene_symbol, f = msig$gs_name)

    #Running fgsea algorithm:
    fgseaRes <- fgseaMultilevel(pathways = msigdbr_list, stats = ranks)

R version 4.1.3 (2022-03-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale:
[1] LC_COLLATE=Dutch_Netherlands.1252  LC_CTYPE=Dutch_Netherlands.1252    LC_MONETARY=Dutch_Netherlands.1252
[4] LC_NUMERIC=C                       LC_TIME=Dutch_Netherlands.1252    

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

other attached packages:
 [1] msigdbr_7.4.1          data.table_1.14.2      fgsea_1.21.2           clusterProfiler_4.2.2  reshape2_1.4.4        
 [6] haven_2.4.3            EnhancedVolcano_1.12.0 ggrepel_0.9.1          readxl_1.3.1           gplots_3.1.1          
[11] RColorBrewer_1.1-2     forcats_0.5.1          stringr_1.4.0          purrr_0.3.4            readr_2.1.2           
[16] tidyr_1.2.0            tibble_3.1.6           ggplot2_3.3.5          tidyverse_1.3.1        dplyr_1.0.8           

loaded via a namespace (and not attached):
  [1] snow_0.4-4             shadowtext_0.1.1       backports_1.4.1        fastmatch_1.1-3        plyr_1.8.6            
  [6] igraph_1.2.11          lazyeval_0.2.2         splines_4.1.3          BiocParallel_1.28.3    GenomeInfoDb_1.30.1   
 [11] digest_0.6.29          yulab.utils_0.0.4      GOSemSim_2.20.0        viridis_0.6.2          GO.db_3.14.0          
 [16] fansi_1.0.2            magrittr_2.0.2         memoise_2.0.1          tzdb_0.2.0             Biostrings_2.62.0     
 [21] graphlayouts_0.8.0     modelr_0.1.8           extrafont_0.17         extrafontdb_1.0        enrichplot_1.14.2     
 [26] colorspace_2.0-3       blob_1.2.2             rvest_1.0.2            xfun_0.24              crayon_1.5.1          
 [31] RCurl_1.98-1.6         jsonlite_1.8.0         scatterpie_0.1.7       ape_5.6-2              glue_1.6.2            
 [36] polyclip_1.10-0        gtable_0.3.0           zlibbioc_1.40.0        XVector_0.34.0         proj4_1.0-11          
 [41] Rttf2pt1_1.3.10        BiocGenerics_0.40.0    maps_3.4.0             scales_1.1.1           DOSE_3.20.1           
 [46] DBI_1.1.2              Rcpp_1.0.8.3           viridisLite_0.4.0      gridGraphics_0.5-1     tidytree_0.3.9        
 [51] bit_4.0.4              stats4_4.1.3           httr_1.4.2             ellipsis_0.3.2         pkgconfig_2.0.3       
 [56] farver_2.1.0           dbplyr_2.1.1           utf8_1.2.2             ggplotify_0.1.0        tidyselect_1.1.2      
 [61] labeling_0.4.2         rlang_1.0.2            AnnotationDbi_1.56.2   munsell_0.5.0          cellranger_1.1.0      
 [66] tools_4.1.3            cachem_1.0.6           downloader_0.4         cli_3.2.0              generics_0.1.2        
 [71] RSQLite_2.2.11         broom_0.7.12           fastmap_1.1.0          ggtree_3.2.1           babelgene_21.4        
 [76] bit64_4.0.5            fs_1.5.2               tidygraph_1.2.0        caTools_1.18.2         KEGGREST_1.34.0       
 [81] ggraph_2.0.5           nlme_3.1-155           ash_1.0-15             ggrastr_1.0.1          aplot_0.1.2           
 [86] DO.db_2.9              xml2_1.3.3             compiler_4.1.3         rstudioapi_0.13        beeswarm_0.4.0        
 [91] png_0.1-7              reprex_2.0.1           treeio_1.18.1          tweenr_1.0.2           stringi_1.7.6         
 [96] ggalt_0.4.0            lattice_0.20-45        Matrix_1.4-1           vctrs_0.3.8            pillar_1.7.0          
[101] lifecycle_1.0.1        bitops_1.0-7           patchwork_1.1.1        qvalue_2.26.0          R6_2.5.1              
[106] KernSmooth_2.23-20     gridExtra_2.3          vipor_0.4.5            IRanges_2.28.0         MASS_7.3-56           
[111] gtools_3.9.2           assertthat_0.2.1       withr_2.5.0            S4Vectors_0.32.3       GenomeInfoDbData_1.2.7
[116] parallel_4.1.3         hms_1.1.1              grid_4.1.3             ggfun_0.0.5            ggforce_0.3.3         
[121] Biobase_2.54.0         lubridate_1.8.0        tinytex_0.35           ggbeeswarm_0.6.0