Missing Ig and TCR genes in human genome

[ye0223]

Hello,

I am using hg19 genome (by addArchRGenome("hg19")) and noticed that Ig or TCR genes are not included in the ArchR project or ArchR Browser. They are annotated distinctly as IG_V/D/J/C_gene or TR_V/D/J/C_gene from other protein coding genes for the biotypes in Ensembl and I assume they got filtered out due to this different biotypes.
Could you include these genes in the annotations?
I'm attaching the images of WashU Epigenome Browser and ArchR Browser and my session Info below.
Thank you in advance for your help!

R version 4.0.2 (2020-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /share/software/user/open/openblas/0.2.19/lib/libopenblasp-r0.2.19.so

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

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

other attached packages:
 [1] gtable_0.3.0                ggrepel_0.9.1               rhandsontable_0.3.7         shiny_1.6.0                
 [5] ggpubr_0.4.0                SeuratObject_4.0.0          Seurat_4.0.1                forcats_0.5.1              
 [9] stringr_1.4.0               dplyr_1.0.5                 purrr_0.3.4                 readr_1.4.0                
[13] tidyr_1.1.3                 tibble_3.1.0                tidyverse_1.3.0             ArchR_1.0.0                
[17] magrittr_2.0.1              rhdf5_2.34.0                Matrix_1.2-18               data.table_1.14.0          
[21] SummarizedExperiment_1.20.0 Biobase_2.50.0              GenomicRanges_1.42.0        GenomeInfoDb_1.26.4        
[25] IRanges_2.24.1              S4Vectors_0.28.1            BiocGenerics_0.36.0         MatrixGenerics_1.2.1       
[29] matrixStats_0.58.0          ggplot2_3.3.3              

loaded via a namespace (and not attached):
  [1] utf8_1.2.1             reticulate_1.18        tidyselect_1.1.0       htmlwidgets_1.5.3     
  [5] grid_4.0.2             Rtsne_0.15             munsell_0.5.0          codetools_0.2-16      
  [9] ica_1.0-2              future_1.21.0          miniUI_0.1.1.1         withr_2.4.1           
 [13] colorspace_2.0-0       rstudioapi_0.13        ROCR_1.0-11            ggsignif_0.6.1        
 [17] tensor_1.5             listenv_0.8.0          labeling_0.4.2         GenomeInfoDbData_1.2.4
 [21] polyclip_1.10-0        farver_2.1.0           parallelly_1.24.0      vctrs_0.3.7           
 [25] generics_0.1.0         R6_2.5.0               clue_0.3-58            bitops_1.0-6          
 [29] rhdf5filters_1.2.0     spatstat.utils_2.1-0   cachem_1.0.4           DelayedArray_0.16.3   
 [33] assertthat_0.2.1       promises_1.2.0.1       scales_1.1.1           Cairo_1.5-12.2        
 [37] globals_0.14.0         goftest_1.2-2          rlang_0.4.10           GlobalOptions_0.1.2   
 [41] splines_4.0.2          rstatix_0.7.0          lazyeval_0.2.2         spatstat.geom_2.0-1   
 [45] broom_0.7.5            yaml_2.2.1             reshape2_1.4.4         abind_1.4-5           
 [49] modelr_0.1.8           backports_1.2.1        httpuv_1.5.5           tools_4.0.2           
 [53] ellipsis_0.3.1         spatstat.core_2.0-0    jquerylib_0.1.3        RColorBrewer_1.1-2    
 [57] ggridges_0.5.3         Rcpp_1.0.6             plyr_1.8.6             zlibbioc_1.36.0       
 [61] RCurl_1.98-1.3         rpart_4.1-15           deldir_0.2-10          pbapply_1.4-3         
 [65] GetoptLong_1.0.5       cowplot_1.1.1          zoo_1.8-9              haven_2.3.1           
 [69] cluster_2.1.0          fs_1.5.0               scattermore_0.7        openxlsx_4.2.3        
 [73] circlize_0.4.12        lmtest_0.9-38          reprex_1.0.0           RANN_2.6.1            
 [77] fitdistrplus_1.1-3     hms_1.0.0              patchwork_1.1.0.9000   mime_0.10             
 [81] xtable_1.8-4           rio_0.5.26             readxl_1.3.1           gridExtra_2.3         
 [85] shape_1.4.5            compiler_4.0.2         KernSmooth_2.23-17     crayon_1.4.1          
 [89] htmltools_0.5.1.1      mgcv_1.8-31            later_1.1.0.1          lubridate_1.7.10      
 [93] DBI_1.1.1              dbplyr_2.1.0           ComplexHeatmap_2.6.2   MASS_7.3-51.6         
 [97] car_3.0-10             cli_2.3.1              igraph_1.2.6           pkgconfig_2.0.3       
[101] foreign_0.8-80         plotly_4.9.3           spatstat.sparse_2.0-0  xml2_1.3.2            
[105] bslib_0.2.4            XVector_0.30.0         rvest_1.0.0            digest_0.6.27         
[109] sctransform_0.3.2.9006 RcppAnnoy_0.0.18       spatstat.data_2.1-0    cellranger_1.1.0      
[113] leiden_0.3.7           uwot_0.1.10            curl_4.3               gtools_3.8.2          
[117] rjson_0.2.20           lifecycle_1.0.0        nlme_3.1-148           jsonlite_1.7.2        
[121] Rhdf5lib_1.12.1        carData_3.0-4          viridisLite_0.3.0      fansi_0.4.2           
[125] pillar_1.5.1           lattice_0.20-41        fastmap_1.1.0          httr_1.4.2            
[129] survival_3.1-12        glue_1.4.2             zip_2.1.1              png_0.1-7             
[133] shinythemes_1.2.0      stringi_1.5.3          sass_0.3.1             irlba_2.3.3           
[137] future.apply_1.7.0    ```

[rcorces]

As described here - https://www.archrproject.com/bookdown/getting-set-up.html
The gene sets associated with your project are derived from a TxDb object. Whatever is in that object should show up in your project. If you want something that isnt included, you will need to find a TxDb object that includes those genes or make one yourself.

[NoemieL]

Hi,
I have the same problem and I would like to know @ye0223 how did you manage to get the Ig and TCR genes in the TxDb object?
Thanks