I would like to process proprietary RNA-Seq data with the same version of the pipeline behind recount3 data (Monorail).

To do so, I downloaded the latest stable versions of recount-pump (v 1.1.3) and recount-unify (v 1.1.1), as suggested in the Monorail github repo.

Now, I would like to retrieve the version of the Monorail pipeline used to generate TCGA data available on Recount3 R package, so that I can process the proprietary data with the same Monorail pipeline version.

I have looked through the official reocunt3 documentation and Recount3 Bioconductor Vignettes, but could not find a way to retrieve the Monorail pipeline version.

Is it the Monorail pipeline version of recount3 R package data available?

Here is the code snippet I am using to download recount3 TCGA data :

library("recount3")

options(recount3_url = "https://recount-opendata.s3.amazonaws.com/recount3/release")

human_projects <- available_projects()

tcga_info = subset(
    human_projects,
    file_source == "tcga" & project_type == "data_sources"
)

rse_tcga <- create_rse(tcga_info)

Here is the output of sessionInfo():

> sessionInfo()
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=Danish_Denmark.1252  LC_CTYPE=Danish_Denmark.1252    LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C                   
[5] LC_TIME=Danish_Denmark.1252    

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

other attached packages:
 [1] recount3_1.6.0              SummarizedExperiment_1.26.1 GenomicRanges_1.48.0        GenomeInfoDb_1.32.4        
 [5] IRanges_2.30.1              MatrixGenerics_1.8.1        matrixStats_1.0.0           data.table_1.14.8          
 [9] msigdbr_7.5.1               fgsea_1.22.0                ggrepel_0.9.3               pheatmap_1.0.12            
[13] Rtsne_0.16                  umap_0.2.10.0               cowplot_1.1.1               reshape2_1.4.4             
[17] scales_1.2.1                knitr_1.43                  GeoMxWorkflows_1.2.0        GeomxTools_3.0.1           
[21] NanoStringNCTools_1.4.0     ggplot2_3.4.2               S4Vectors_0.34.0            Biobase_2.56.0             
[25] BiocGenerics_0.42.0        

loaded via a namespace (and not attached):
  [1] readxl_1.4.3             uuid_1.1-0               snow_0.4-4               fastmatch_1.1-3          BiocFileCache_2.4.0     
  [6] systemfonts_1.0.4        plyr_1.8.8               sp_2.0-0                 splines_4.2.2            BiocParallel_1.30.4     
 [11] listenv_0.9.0            digest_0.6.33            htmltools_0.5.5          lmerTest_3.1-3           fansi_1.0.4             
 [16] magrittr_2.0.3           memoise_2.0.1            globals_0.16.2           Biostrings_2.64.1        R.utils_2.12.2          
 [21] askpass_1.1              colorspace_2.1-0         blob_1.2.4               rappdirs_0.3.3           xfun_0.39               
 [26] dplyr_1.1.2              crayon_1.5.2             RCurl_1.98-1.12          jsonlite_1.8.7           EnvStats_2.8.0          
 [31] lme4_1.1-34              progressr_0.13.0         glue_1.6.2               polyclip_1.10-4          gtable_0.3.3            
 [36] zlibbioc_1.42.0          XVector_0.36.0           DelayedArray_0.22.0      future.apply_1.11.0      DBI_1.1.3               
 [41] GGally_2.1.2             ggthemes_4.2.4           Rcpp_1.0.11              reticulate_1.30          bit_4.0.5               
 [46] htmlwidgets_1.6.2        httr_1.4.6               RColorBrewer_1.1-3       XML_3.99-0.14            pkgconfig_2.0.3         
 [51] reshape_0.8.9            R.methodsS3_1.8.2        farver_2.1.1             sass_0.4.7               dbplyr_2.3.3            
 [56] utf8_1.2.3               tidyselect_1.2.0         labeling_0.4.2           rlang_1.1.1              munsell_0.5.0           
 [61] cellranger_1.1.0         tools_4.2.2              cachem_1.0.8             cli_3.6.1                generics_0.1.3          
 [66] RSQLite_2.3.1            evaluate_0.21            stringr_1.5.0            fastmap_1.1.1            yaml_2.3.7              
 [71] outliers_0.15            babelgene_22.9           bit64_4.0.5              purrr_1.0.1              future_1.33.0           
 [76] nlme_3.1-162             R.oo_1.25.0              ggiraph_0.8.7            BiocStyle_2.24.0         compiler_4.2.2          
 [81] beeswarm_0.4.0           filelock_1.0.2           curl_5.0.1               png_0.1-8                tibble_3.2.1            
 [86] tweenr_2.0.2             bslib_0.5.0              stringi_1.7.12           RSpectra_0.16-1          lattice_0.21-8          
 [91] Matrix_1.5-5             nloptr_2.0.3             vctrs_0.6.3              pillar_1.9.0             lifecycle_1.0.3         
 [96] BiocManager_1.30.21.1    jquerylib_0.1.4          bitops_1.0-7             rtracklayer_1.56.1       BiocIO_1.6.0            
[101] R6_2.5.1                 gridExtra_2.3            vipor_0.4.5              parallelly_1.36.0        sessioninfo_1.2.2       
[106] codetools_0.2-19         boot_1.3-28.1            MASS_7.3-60              openssl_2.1.0            rjson_0.2.21            
[111] withr_2.5.0              SeuratObject_4.1.3       GenomicAlignments_1.32.1 Rsamtools_2.12.0         GenomeInfoDbData_1.2.8  
[116] parallel_4.2.2           grid_4.2.2               minqa_1.2.5              rmarkdown_2.23           ggforce_0.4.1           
[121] numDeriv_2016.8-1.1      ggbeeswarm_0.7.2         restfulr_0.0.15

Hi Lorenzo,

Sorry for the delay, I just saw this today.

You have the correct recount pump and unify image versions for generating recount3-compatible data from Monorail (v 1.1.3 and v 1.1.1)

While there have been minor changes (mainly to the SRA download module) these don't impact the compatibility of the outputs of the Monorail pipeline, so you should be fine running those image versions on your data.

For faster responses for Monorail-related questions, please post an issue under: https://github.com/langmead-lab/monorail-external

Thanks, Chris