Hi all,

I'm trying to visualize some results of an enrichment analysis on two datasets but but I keep having the same error:

> dotplot(merge_dataset_1_and_dataset_2, showCategory = 10)
Error in `$<-.data.frame`(`*tmp*`, "Cluster", value = NA_integer_) : 
  replacement has 1 row, data has 0

The obj mergedataset1anddataset2 is the merge between the gseaResult of dataset1 and the gseaResult of dataset2 on GO MSigDB Collection:

> str(merge_dataset_1_and_dataset_2)
Formal class 'compareClusterResult' [package "clusterProfiler"] with 4 slots
  ..@ compareClusterResult:'data.frame':    11303 obs. of  12 variables:
  .. ..$ Cluster        : Factor w/ 2 levels "Dataset_1","Dataset_2": 1 1 1 1 1 1 1 1 1 1 ...
  .. ..$ ID             : chr [1:11303] "GO_CATION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY" "GO_METAL_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY" "GO_CHEMICAL_SYNAPTIC_TRANSMISSION_POSTSYNAPTIC" "GO_LEUKOCYTE_APOPTOTIC_PROCESS" ...
  .. ..$ Description    : chr [1:11303] "GO_CATION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY" "GO_METAL_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY" "GO_CHEMICAL_SYNAPTIC_TRANSMISSION_POSTSYNAPTIC" "GO_LEUKOCYTE_APOPTOTIC_PROCESS" ...
  .. ..$ setSize        : int [1:11303] 434 281 69 78 31 22 23 21 17 17 ...
  .. ..$ enrichmentScore: num [1:11303] -0.356 -0.353 -0.488 -0.47 -0.635 ...
  .. ..$ NES            : num [1:11303] -1.56 -1.49 -1.75 -1.7 -1.95 ...
  .. ..$ pvalue         : num [1:11303] 0.00113 0.00121 0.00143 0.00144 0.00163 ...
  .. ..$ p.adjust       : num [1:11303] 0.385 0.385 0.385 0.385 0.385 ...
  .. ..$ qvalues        : num [1:11303] 0.373 0.373 0.373 0.373 0.373 ...
  .. ..$ rank           : num [1:11303] 2011 1996 3447 1746 1810 ...
  .. ..$ leading_edge   : chr [1:11303] "tags=20%, list=13%, signal=18%" "tags=20%, list=13%, signal=18%" "tags=39%, list=22%, signal=30%" "tags=26%, list=11%, signal=23%" ...
  .. ..$ core_enrichment: chr [1:11303] "SLC36A2/CNNM2/SLC6A2/SLC45A4/SLC39A14/SLC11A2/SCN3B/CACNA1C/SLC13A2/SLC25A45/KCNJ13/KCNK16/ATP2A3/SLC1A3/KCNB1/"| __truncated__ "CNNM2/SLC6A2/SLC39A14/SLC11A2/SCN3B/CACNA1C/SLC13A2/KCNJ13/KCNK16/ATP2A3/SLC1A3/KCNB1/KCNAB2/KCNA3/SCNN1A/KCNMB"| __truncated__ "MECP2/ZMYND8/GLRB/CHRNA10/ADORA2A/APP/RGS4/MAPK8IP2/ADORA1/EIF4A3/SLC29A1/PPP3CA/OPRM1/P2RX2/GRIN2D/CHRNE/HCRT/"| __truncated__ "TNFRSF4/BAX/PDCD1/CD74/CXCR2/SLC46A2/NFKBID/MEF2C/ANXA1/PTCRA/HIF1A/GAS6/FOXP1/DFFA/NOC2L/MIF/EFNA1/CRKL/MERTK/CTSL" ...
  ..@ geneClusters        : list()
  ..@ fun                 : chr(0) 
  ..@ .call               : language `<undef>`()

Then I repeated processing the clusterProfiler sample code I had seen long ago and the dotplot () of this works well in my session. The structure of the merge_example seems completely similar, the only thing is that in the example the merge is between enrichResult objs:

 > str(merge_example)
Formal class 'compareClusterResult' [package "clusterProfiler"] with 4 slots
  ..@ compareClusterResult:'data.frame':    126 obs. of  10 variables:
  .. ..$ Cluster    : Factor w/ 2 levels "david","clusterProfiler": 1 1 1 1 1 1 1 1 1 1 ...
  .. ..$ ID         : chr [1:126] "GO:0006614" "GO:0006613" "GO:0045047" "GO:0072599" ...
  .. ..$ Description: chr [1:126] "SRP-dependent cotranslational protein targeting to membrane" "cotranslational protein targeting to membrane" "protein targeting to ER" "establishment of protein localization to endoplasmic reticulum" ...
  .. ..$ GeneRatio  : chr [1:126] "24/186" "24/186" "24/186" "24/186" ...
  .. ..$ BgRatio    : chr [1:126] "96/16792" "103/16792" "104/16792" "108/16792" ...
  .. ..$ pvalue     : num [1:126] 9.54e-25 5.56e-24 7.07e-24 1.80e-23 1.55e-22 ...
  .. ..$ p.adjust   : num [1:126] 3.05e-21 8.88e-21 7.53e-21 1.44e-20 9.88e-20 ...
  .. ..$ qvalue     : num [1:126] 2.29e-22 5.65e-22 5.65e-22 1.08e-21 7.43e-21 ...
  .. ..$ geneID     : chr [1:126] "ENSG00000174444/ENSG00000198242/ENSG00000188846/ENSG00000166441/ENSG00000198918/ENSG00000105193/ENSG00000148303"| __truncated__ "ENSG00000174444/ENSG00000198242/ENSG00000188846/ENSG00000166441/ENSG00000198918/ENSG00000105193/ENSG00000148303"| __truncated__ "ENSG00000174444/ENSG00000198242/ENSG00000188846/ENSG00000166441/ENSG00000198918/ENSG00000105193/ENSG00000148303"| __truncated__ "ENSG00000174444/ENSG00000198242/ENSG00000188846/ENSG00000166441/ENSG00000198918/ENSG00000105193/ENSG00000148303"| __truncated__ ...
  .. ..$ Count      : int [1:126] 24 24 24 24 28 28 24 27 24 28 ...
  ..@ geneClusters        : list()
  ..@ fun                 : chr(0) 
  ..@ .call               : language `<undef>`()
> dotplot(merge_example, showCategory = 10)

If the two structures are similar, why does the dotplot () on the merge of my analysis fail? What is wrong?

Thanks in advance, Regards Giovanni

> sessionInfo()
R version 3.6.2 (2019-12-12)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.6 LTS

Matrix products: default
BLAS:   /usr/local/lib/R/lib/libRblas.so
LAPACK: /usr/local/lib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=it_IT.UTF-8          LC_NUMERIC=C                  LC_TIME=it_IT.UTF-8           LC_COLLATE=it_IT.UTF-8       
 [5] LC_MONETARY=it_IT.UTF-8       LC_MESSAGES=it_IT.UTF-8       LC_PAPER=it_IT.UTF-8          LC_NAME=it_IT.UTF-8          
 [9] LC_ADDRESS=it_IT.UTF-8        LC_TELEPHONE=it_IT.UTF-8      LC_MEASUREMENT=it_IT.UTF-8    LC_IDENTIFICATION=it_IT.UTF-8

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

other attached packages:
 [1] openxlsx_4.1.5          RDAVIDWebService_1.24.0 ggplot2_3.3.0           GOstats_2.52.0          Category_2.52.1        
 [6] Matrix_1.2-18           graph_1.64.0            org.Hs.eg.db_3.10.0     AnnotationDbi_1.48.0    IRanges_2.20.2         
[11] S4Vectors_0.24.4        Biobase_2.46.0          BiocGenerics_0.32.0     magrittr_1.5            dplyr_0.8.5            
[16] dbplyr_1.4.4            limma_3.42.2            DOSE_3.12.0             clusterProfiler_3.14.3 

loaded via a namespace (and not attached):
 [1] bitops_1.0-6           enrichplot_1.6.1       bit64_0.9-7            RColorBrewer_1.1-2     progress_1.2.2         httr_1.4.1            
 [7] Rgraphviz_2.30.0       tools_3.6.2            R6_2.4.1               DBI_1.1.0              colorspace_1.4-1       withr_2.2.0           
[13] tidyselect_1.1.0       gridExtra_2.3          prettyunits_1.1.1      bit_1.1-15.2           compiler_3.6.2         cli_2.0.2             
[19] xml2_1.3.2             labeling_0.3           triebeard_0.3.0        scales_1.1.1           genefilter_1.68.0      RBGL_1.62.1           
[25] ggridges_0.5.2         stringr_1.4.0          digest_0.6.25          AnnotationForge_1.28.0 pkgconfig_2.0.3        rlang_0.4.6           
[31] rstudioapi_0.11        RSQLite_2.2.0          gridGraphics_0.5-0     farver_2.0.3           jsonlite_1.6.1         BiocParallel_1.20.1   
[37] zip_2.0.4              GOSemSim_2.12.1        RCurl_1.98-1.2         ggplotify_0.0.5        GO.db_3.10.0           Rcpp_1.0.4.6          
[43] munsell_0.5.0          fansi_0.4.1            viridis_0.5.1          lifecycle_0.2.0        stringi_1.4.6          yaml_2.2.1            
[49] ggraph_2.0.3           MASS_7.3-51.6          plyr_1.8.6             qvalue_2.18.0          grid_3.6.2             blob_1.2.1            
[55] ggrepel_0.8.2          DO.db_2.9              crayon_1.3.4           lattice_0.20-41        graphlayouts_0.7.0     cowplot_1.0.0         
[61] splines_3.6.2          annotate_1.64.0        hms_0.5.3              pillar_1.4.4           fgsea_1.12.0           igraph_1.2.5          
[67] reshape2_1.4.4         fastmatch_1.1-0        XML_3.99-0.3           glue_1.4.1             data.table_1.12.8      BiocManager_1.30.10   
[73] vctrs_0.3.0            tweenr_1.0.1           urltools_1.7.3         gtable_0.3.0           purrr_0.3.4            polyclip_1.10-0       
[79] tidyr_1.1.0            assertthat_0.2.1       ggforce_0.3.1          europepmc_0.3          xtable_1.8-4           tidygraph_1.2.0       
[85] survival_3.1-12        viridisLite_0.3.0      tibble_3.0.1           rJava_0.9-12           rvcheck_0.1.8          memoise_1.1.0         
[91] ellipsis_0.3.1         GSEABase_1.48.0