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Generally Applicable Gene-set Enrichment for Pathway Analysis
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Error in tutorial RNA-Seq Data Pathway: summarizeOverlaps returns 'data' must be of a vector type, was 'NULL' #2

Open angiachino opened 3 years ago

angiachino commented 3 years ago

I am working through the tutorial about RNA-Seq Data Pathway and Gene-set Analysis Workflows but the "Quick start" example is not running correctly in my system. Specifically, it gets stuck at the summarizeOverlaps step, where the following error occurs:

Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x),  : 
  'data' must be of a vector type, was 'NULL'

Here is the code I am running (lifted verbatim from the tutorial):

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
exByGn <- exonsBy(TxDb.Hsapiens.UCSC.hg19.knownGene, "gene")
library(GenomicAlignments)
fls <- list.files("tophat_all/", pattern="bam$", full.names =T)
bamfls <- BamFileList(fls)
flag <- scanBamFlag(isSecondaryAlignment=FALSE, isProperPair=TRUE)
param <- ScanBamParam(flag=flag)
gnCnt <- summarizeOverlaps(exByGn, bamfls, mode="Union",
                             ignore.strand=TRUE, singleEnd=FALSE, param=param)

This is the result of running traceback() after the error occurs:

8: array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), 
       NULL) else NULL)
7: as.matrix.default(do.call(cbind, cts))
6: as.matrix(do.call(cbind, cts))
5: as.matrix(do.call(cbind, cts))
4: .dispatchBamFiles(features, reads, mode, ignore.strand, inter.feature = inter.feature, 
       singleEnd = singleEnd, fragments = fragments, param = param, 
       preprocess.reads = preprocess.reads, ...)
3: .local(features, reads, mode, ignore.strand, ...)
2: summarizeOverlaps(exByGn, bamfls, mode = "Union", ignore.strand = TRUE, 
       singleEnd = FALSE, param = param)
1: summarizeOverlaps(exByGn, bamfls, mode = "Union", ignore.strand = TRUE, 
       singleEnd = FALSE, param = param)

And this is my sessionInfo in case it helps:

R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

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

other attached packages:
 [1] GenomicAlignments_1.28.0                Rsamtools_2.8.0                        
 [3] Biostrings_2.60.2                       XVector_0.32.0                         
 [5] SummarizedExperiment_1.22.0             MatrixGenerics_1.4.2                   
 [7] matrixStats_0.60.0                      TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
 [9] GenomicFeatures_1.44.0                  AnnotationDbi_1.54.1                   
[11] Biobase_2.52.0                          GenomicRanges_1.44.0                   
[13] GenomeInfoDb_1.28.1                     IRanges_2.26.0                         
[15] S4Vectors_0.30.0                        BiocGenerics_0.38.0                    

loaded via a namespace (and not attached):
  [1] estimability_1.3              rappdirs_0.3.3                rtracklayer_1.52.0           
  [4] pbdZMQ_0.3-5                  R.methodsS3_1.8.1             tidyr_1.1.3                  
  [7] ggplot2_3.3.5                 bit64_4.0.5                   knitr_1.33                   
 [10] DelayedArray_0.18.0           R.utils_2.10.1                data.table_1.14.0            
 [13] rpart_4.1-15                  KEGGREST_1.32.0               RCurl_1.98-1.3               
 [16] AnnotationFilter_1.16.0       generics_0.1.0                cowplot_1.1.1                
 [19] RSQLite_2.2.7                 shadowtext_0.0.8              chron_2.3-56                 
 [22] bit_4.0.4                     enrichplot_1.12.2             base64url_1.4                
 [25] xml2_1.3.2                    httpuv_1.6.1                  assertthat_0.2.1             
 [28] viridis_0.6.1                 xfun_0.25                     hms_1.1.0                    
 [31] evaluate_0.14                 promises_1.2.0.1              DEoptimR_1.0-9               
 [34] fansi_0.5.0                   restfulr_0.0.13               progress_1.2.2               
 [37] caTools_1.18.2                dendextend_1.15.1             dbplyr_2.1.1                 
 [40] readxl_1.3.1                  igraph_1.2.6                  DBI_1.1.1                    
 [43] geneplotter_1.70.0            htmlwidgets_1.5.3             purrr_0.3.4                  
 [46] ellipsis_0.3.2                crosstalk_1.1.1               RCytoscape_1.24.1            
 [49] dplyr_1.0.7                   backports_1.2.1               signal_0.7-7                 
 [52] annotate_1.70.0               biomaRt_2.48.2                vctrs_0.3.8                  
 [55] ensembldb_2.16.4              abind_1.4-5                   cachem_1.0.5                 
 [58] ggforce_0.3.3                 Gviz_1.36.2                   BSgenome_1.60.0              
 [61] robustbase_0.93-8             checkmate_2.0.0               emmeans_1.6.2-1              
 [64] treeio_1.16.1                 prettyunits_1.1.1             cluster_2.1.2                
 [67] DOSE_3.18.1                   fuzzyjoin_0.1.6               pacman_0.5.1                 
 [70] ape_5.5                       IRdisplay_1.0                 lazyeval_0.2.2               
 [73] crayon_1.4.1                  SetRank_1.1.0                 uchardet_1.1.0               
 [76] genefilter_1.74.0             pkgconfig_2.0.3               tweenr_1.0.2                 
 [79] qpcR_1.4-1                    nlme_3.1-152                  ProtGenerics_1.24.0          
 [82] nnet_7.3-16                   rlang_0.4.11                  RJSONIO_1.3-1.4              
 [85] lifecycle_1.0.0               downloader_0.4                filelock_1.0.2               
 [88] BiocFileCache_2.0.0           regutools_1.4.0               AnnotationHub_3.0.1          
 [91] dichromat_2.0-0               polyclip_1.10-0               cellranger_1.1.0             
 [94] graph_1.70.0                  aplot_0.0.6                   Matrix_1.3-4                 
 [97] IRkernel_1.2                  carData_3.0-4                 boot_1.3-28                  
[100] base64enc_0.1-3               png_0.1-7                     viridisLite_0.4.0            
[103] rjson_0.2.20                  bitops_1.0-7                  R.oo_1.24.0                  
[106] KernSmooth_2.23-20            dplR_1.7.2                    blob_1.2.2                   
[109] rgl_0.107.10                  afex_1.0-1                    stringr_1.4.0                
[112] qvalue_2.24.0                 jpeg_0.1-9                    scales_1.1.1                 
[115] memoise_2.0.0                 magrittr_2.0.1                plyr_1.8.6                   
[118] gplots_3.1.1                  zlibbioc_1.38.0               scatterpie_0.1.6             
[121] compiler_4.1.0                BiocIO_1.2.0                  RColorBrewer_1.1-2           
[124] lme4_1.1-27.1                 DESeq2_1.32.0                 lmerTest_3.1-3               
[127] patchwork_1.1.1               htmlTable_2.2.1               Formula_1.2-4                
[130] MASS_7.3-54                   tidyselect_1.1.1              stringi_1.7.3                
[133] forcats_0.5.1                 XMLRPC_0.3-0                  gage_2.42.0                  
[136] yaml_2.2.1                    GOSemSim_2.18.1               locfit_1.5-9.4               
[139] ggrepel_0.9.1                 latticeExtra_0.6-29           grid_4.1.0                   
[142] VariantAnnotation_1.38.0      fastmatch_1.1-3               tools_4.1.0                  
[145] rio_0.5.27                    rstudioapi_0.13               uuid_0.1-4                   
[148] foreign_0.8-81                genbankr_1.20.0               gridExtra_2.3                
[151] farver_2.1.0                  ggraph_2.0.5                  rvcheck_0.1.8                
[154] digest_0.6.27                 BiocManager_1.30.16           shiny_1.6.0                  
[157] Rcpp_1.0.7                    car_3.0-11                    BiocVersion_3.13.1           
[160] later_1.2.0                   httr_1.4.2                    minpack.lm_1.2-1             
[163] biovizBase_1.40.0             ReadqPCR_1.38.0               colorspace_2.0-2             
[166] XML_3.99-0.6                  splines_4.1.0                 tidytree_0.3.4               
[169] graphlayouts_0.7.1            xtable_1.8-4                  ggtree_3.0.2                 
[172] jsonlite_1.7.2                nloptr_1.2.2.2                tidygraph_1.2.0              
[175] R6_2.5.0                      Hmisc_4.5-0                   pillar_1.6.2                 
[178] htmltools_0.5.1.1             mime_0.11                     NormqPCR_1.38.0              
[181] glue_1.4.2                    fastmap_1.1.0                 minqa_1.2.4                  
[184] clusterProfiler_4.0.2         BiocParallel_1.26.1           interactiveDisplayBase_1.30.0
[187] fgsea_1.18.0                  mvtnorm_1.1-2                 utf8_1.2.2                   
[190] lattice_0.20-44               tibble_3.1.3                  numDeriv_2016.8-1.1          
[193] curl_4.3.2                    gtools_3.9.2                  RamiGO_1.22.0                
[196] zip_2.2.0                     GO.db_3.13.0                  openxlsx_4.2.4               
[199] survival_3.2-11               repr_1.1.3                    munsell_0.5.0                
[202] DO.db_2.9                     GenomeInfoDbData_1.2.6        RCy3_2.12.3                  
[205] haven_2.4.3                   reshape2_1.4.4                gtable_0.3.0

I have checked the version of all packages and the Bioconductor release and everything seems up-to-date. I have done a bit of browsing and I notice that this same error popped up back in 2016 in http://seqanswers.com/forums/archive/index.php/t-64313.html but at that time it was not solved.

Any advice on how I should proceed? If I can't even go through the tutorial I doubt I will be able to use the package on my own data.

raw937 commented 1 year ago

You should try our new pathwrap for RNAseq data. https://github.com/Kannapolis-Bioinformatics/pathwrap