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pipe19's Introduction

pipe19

Large scale sequencing of SARS-CoV-2 in Region Midtjylland, Denmark

Pipeline overview

We use the Artic V3 primers to amplify 98 overlapping amplicons. The amplicons are then fragmented and we sequence each isolate with QiaSeq on Illumina NextSeq and NovaSeq platforms at the local Department of Molecular Medicine.
This pipeline accepts the demultiplexed data from this sequencing protocol and generally follows the iVar consensus pipeline:

Steps:

  • Trim index-adaptors from reads with trim-galore.
  • Map reads with bwa mem.
  • Trim primer regions from alignment with iVar trim.
  • Call consensus with iVar consensus (read-depth >= 10, base-frequency >= 0.8).
  • Call lineage with Pangolin.
  • Call clade with Nextclade.

For each batch of samples, the following is done:

  • Integration of file metadata, pangolin and nextclade calls.
  • Compression of raw- and consensus data, tailored for upload.
  • Generation of a QC/surveillance report.

Dependencies:

  • Singularity (or a similar docker-compatible platform)
  • Python 3.7
    • yaml (pyyaml)
    • pandas
    • gwf (gwf-org)

Setup

  1. Clone the repo into the dir where you want its base to be: git clone [email protected]:cmkobel/pipe19.git

  2. Install dependencies listed in conda_env.yml: conda env create -f conda_env.yml

  3. Set up your local parameters in the config_example.yaml file.

pipe19's People

Contributors

cmkobel avatar marcmtk avatar

Stargazers

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Watchers

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Forkers

kma-aarhus

pipe19's Issues

Report issue: ✖ object 'C222T' not found ?

stderr output from running b3_report on batch 210223:

Quitting from lines 162-201 (seq_report.Rmd) 
Error: Problem with `mutate()` input `missing_vector`.
✖ object 'C222T' not found
ℹ Input `missing_vector` is `map(...)`.
Backtrace:
     █
  1. ├─(function (file, local = FALSE, echo = verbose, print.eval = echo, ...
  2. │ ├─base::withVisible(eval(ei, envir))
  3. │ └─base::eval(ei, envir)
  4. │   └─base::eval(ei, envir)
  5. ├─base::sapply(opt$FILES, renderArg) /usr/local/bin/render.r:44:0
  6. │ └─base::lapply(X = X, FUN = FUN, ...)
  7. │   └─global::FUN(X[[i]], ...)
  8. │     ├─rmarkdown::render(p) /usr/local/bin/render.r:36:4
  9. │     │ └─knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
 10. │     │   └─knitr:::process_file(text, output)
 11. │     │     ├─base::withCallingHandlers(...)
 12. │     │     ├─knitr:::process_group(group)
 13. │     │     └─knitr:::process_group.block(group)
 14. │     │       └─knitr:::call_block(x)
 15. │     │         └─knitr:::block_exec(params)
 16. │     │           ├─knitr:::in_dir(...)
 17. │     │           └─knitr:::evaluate(...)
 18. │     │             └─evaluate::evaluate(...)
 19. │     │               └─evaluate:::evaluate_call(...)
 20. │     │                 ├─evaluate:::timing_fn(...)
 21. │     │                 ├─base:::handle(...)
 22. │     │                 ├─base::withCallingHandlers(...)
 23. │     │                 ├─base::withVisible(eval(expr, envir, enclos))
 24. │     │                 └─base::eval(expr, envir, enclos)
 25. │     │                   └─base::eval(expr, envir, enclos)
 26. │     └─`%>%`(...)
 27. ├─dplyr::filter(., as.integer(totalMissing) < 3000, date > lubridate::ymd("2020-12-01"))
 28. ├─dplyr::mutate(...)
 29. ├─dplyr:::mutate.data.frame(...)
 30. │ └─dplyr:::mutate_cols(.data, ...)
 31. │   ├─base::withCallingHandlers(...)
 32. │   └─mask$eval_all_mutate(dots[[i]])
 33. ├─purrr::map(...)
 34. │ └─.f(.x[[i]], ...)
 35. │   └─base::eval(parse(text = paste("c(", gsub("\\-", ":", .x), ")")))
 36. │     └─base::eval(parse(text = paste("c(", gsub("\\-", ":", .x), ")")))
 37. └─base::.handleSimpleError(...)
 38.   └─dplyr:::h(simpleError(msg, call))
Warning message:
In grSoftVersion() :
  unable to load shared object '/usr/local/lib/R/modules//R_X11.so':
  libXt.so.6: cannot open shared object file: No such file or directory

Pivot all delimited-value outputs.

Når resultater kommer ud af nextclade og pangolin, var det smart at filerne bliver pivoteret langt.
Fordelen er, at de så bare kan cattes sammen, uden fare for at krydskontaminere kolonner når nye udgaver af værktøjerne ruller ud.

Sequence report størrelse

seq_report.html rundsendt på mail (automail) med target b3_report fylder i skrivende stund 8MB.

Jeg tror grænsen for email-vedhæftninger er omkring 25MB, så vi skal overveje en form for kompression eller lignende på længere sigt.

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