Hi,

I am following the vignette (https://bioconductor.org/packages/devel/bioc/vignettes/SpliceWiz/inst/doc/SW_QuickStart.html).

The reference files I used are "Homo_sapiens.GRCh38.111.gtf" and "Homo_sapiens.GRCh38.dna.primary_assembly.fa" from Ensembl. They contain information for all the chromosomes.

In the pb_output folder, I can see that there are reads and hits in every chromsome.

However, after the differential analysis, I can only see events detected in chromosome 1.

se_2 <- makeSE(nxtse_path_2)

# Assigning annotations to samples
colData(se_2)$condition <- rep(c("Control", Treated"), each = 3)
colData(se_2)$batch <- rep(c("1", "2", "3"), 2)

# Filtering high-confidence events
se_2.filtered <- se_2[applyFilters(se_2),]

# Performing differential analysis
require("edgeR")
res_edgeR_2 <- ASE_edgeR(
    se = se_2.filtered,
    test_factor = "condition",
    test_nom = "Treated",
    test_denom = "Control"
)

For example:

# Check event region
head(res_edgeR_2$EventRegion,5)
[1] "1:151346607-151347210/-" "1:161043361-161045857/-" "1:154602627-154627953/-" "1:154602627-154627854/-" "1:12580667-12617153/-"

All the EventRegions are started by 1:.

I would like to ask where seems to be the problem? Is there a way to check into se_2 or other dataset to see if the differential analysis was properly performed?

Thank you so much for any help!

Best,

Yingying

sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.3

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/New_York
tzcode source: internal

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

other attached packages:
[1] edgeR_4.0.9      limma_3.58.1     fstcore_0.9.18   SpliceWiz_1.4.1  NxtIRFdata_1.8.0

loaded via a namespace (and not attached):
  [1] splines_4.3.2                 later_1.3.2                   BiocIO_1.12.0                 bitops_1.0-7                 
  [5] filelock_1.0.3                tibble_3.2.1                  R.oo_1.25.0                   XML_3.99-0.16                
  [9] lifecycle_1.0.4               lattice_0.22-5                dendextend_1.17.1             magrittr_2.0.3               
 [13] plotly_4.10.4                 sass_0.4.8                    rmarkdown_2.25                jquerylib_0.1.4              
 [17] yaml_2.3.8                    httpuv_1.6.13                 DBI_1.2.0                     RColorBrewer_1.1-3           
 [21] abind_1.4-5                   zlibbioc_1.48.0               rvest_1.0.3                   GenomicRanges_1.54.1         
 [25] purrr_1.0.2                   R.utils_2.12.3                BiocGenerics_0.48.1           RCurl_1.98-1.14              
 [29] rappdirs_0.3.3                seriation_1.5.4               GenomeInfoDbData_1.2.11       IRanges_2.36.0               
 [33] S4Vectors_0.40.2              genefilter_1.84.0             pheatmap_1.0.12               annotate_1.80.0              
 [37] DelayedMatrixStats_1.24.0     codetools_0.2-19              DelayedArray_0.28.0           DT_0.31                      
 [41] xml2_1.3.6                    tidyselect_1.2.0              rhandsontable_0.3.8           viridis_0.6.4                
 [45] TSP_1.2-4                     shinyWidgets_0.8.1            matrixStats_1.2.0             stats4_4.3.2                 
 [49] BiocFileCache_2.10.1          webshot_0.5.5                 GenomicAlignments_1.38.1      jsonlite_1.8.8               
 [53] fst_0.9.8                     ellipsis_0.3.2                survival_3.5-7                iterators_1.0.14             
 [57] foreach_1.5.2                 tools_4.3.2                   progress_1.2.3                Rcpp_1.0.12                  
 [61] glue_1.7.0                    gridExtra_2.3                 SparseArray_1.2.3             xfun_0.41                    
 [65] MatrixGenerics_1.14.0         GenomeInfoDb_1.38.5           dplyr_1.1.4                   ca_0.71.1                    
 [69] HDF5Array_1.30.0              shinydashboard_0.7.2          withr_3.0.0                   BiocManager_1.30.22          
 [73] fastmap_1.1.1                 rhdf5filters_1.14.1           fansi_1.0.6                   digest_0.6.34                
 [77] R6_2.5.1                      mime_0.12                     colorspace_2.1-0              GO.db_3.18.0                 
 [81] RSQLite_2.3.4                 R.methodsS3_1.8.2             utf8_1.2.4                    tidyr_1.3.0                  
 [85] generics_0.1.3                data.table_1.14.10            rtracklayer_1.62.0            prettyunits_1.2.0            
 [89] httr_1.4.7                    htmlwidgets_1.6.4             S4Arrays_1.2.0                pkgconfig_2.0.3              
 [93] gtable_0.3.4                  blob_1.2.4                    registry_0.5-1                XVector_0.42.0               
 [97] htmltools_0.5.7               scales_1.3.0                  Biobase_2.62.0                ompBAM_1.6.0                 
[101] Rsubread_2.16.0               png_0.1-8                     knitr_1.45                    rstudioapi_0.15.0            
[105] rjson_0.2.21                  curl_5.2.0                    cachem_1.0.8                  rhdf5_2.46.1                 
[109] BiocVersion_3.18.1            parallel_4.3.2                AnnotationDbi_1.64.1          restfulr_0.0.15              
[113] pillar_1.9.0                  grid_4.3.2                    vctrs_0.6.5                   promises_1.2.1               
[117] shinyFiles_0.9.3              dbplyr_2.4.0                  xtable_1.8-4                  evaluate_0.23                
[121] cli_3.6.2                     locfit_1.5-9.8                compiler_4.3.2                Rsamtools_2.18.0             
[125] rlang_1.1.3                   crayon_1.5.2                  heatmaply_1.5.0               fs_1.6.3                     
[129] stringi_1.8.3                 viridisLite_0.4.2             BiocParallel_1.36.0           assertthat_0.2.1             
[133] munsell_0.5.0                 Biostrings_2.70.1             lazyeval_0.2.2                Matrix_1.6-5                 
[137] BSgenome_1.70.1               hms_1.1.3                     patchwork_1.2.0               sparseMatrixStats_1.14.0     
[141] bit64_4.0.5                   ggplot2_3.4.4                 Rhdf5lib_1.24.1               KEGGREST_1.42.0              
[145] statmod_1.5.0                 shiny_1.8.0                   SummarizedExperiment_1.32.0   interactiveDisplayBase_1.40.0
[149] AnnotationHub_3.10.0          memoise_2.0.1                 bslib_0.6.1                   bit_4.0.5

Although not fully documented, one can view the reference that accompanies the NxtSE object by calling the following:

embedded_ref <- ref(se_2)

This returns a list containing a seqInfo object and a number of data tables that summarizes the reference that is used to build the NxtSE object

names(embedded_ref)
[1] "seqInfo"     "geneList"    "elements"    "transcripts" "spliceList"  "IRList"     
[7] "ontology"

To verify the chromosomes covered, simply view the seqInfo object:

embedded_ref$seqInfo

The fact that only chomosome 1 appears in differential analysis highly suggests that the source reference only contains annotations for chromosome 1, and has nothing to do with the differential analysis steps.

One can confirm this by viewing the genes in the source reference:

geneList <- viewGenes("/path/to/Reference")
unique(geneList$seqnames)

Hope this helps!