RAMPART v1.1.0 released

Bioinformatics
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A new version of RAMPART, our software for analyzing nanopore data in real-time, is now available. This brings a number of major changes which should help with SARS-CoV-2 analyses. There are no changes to how RAMPART is run.

It’s been great to see so many groups using the ARTIC protocols and RAMPART recently. Please get in touch with any comments of questions via this thread, GitHub or twitter.

v1.1.0 major changes

  • Guppy-demuxed FASTQs can now be used. If this is the case, then porechop is no longer a requirement for RAMPART to run.
  • The memory footprint has been drastically reduced. Testing with 1 million SARS-CoV-2 reads results in only ~20Mb for the server and ~10Mb for the client. Achieving this necessitated the removal of filtering & the ability to change barcode-sample names via the UI. We hope to bring back this functionality in a future release.
  • Bugs in the “Export Reads” pipeline should now be fixed.
  • Improved installation documentation

v1.1.0 minor changes:

  • FASTQs can now be in nested folders (currently 2 levels are allowed)
  • Light and Dark themes are now available and may be changed via a toggle in the header.
  • We now display the version number in the footer to help with bug reports & debugging.
  • Various other minor bugfixes and improvements.

If there are any bugs or feature requests, please make an issue in the RAMPART GitHub repo and we’ll try to improve things. If you are able to contribute to development your help would be extremely welcome.

How to install

Inside the artic-ncov2019 conda environment, you can install via:

conda install -y artic-network::rampart==1.1.0

If there are any issues, you may reinstall the version of RAMPART which came before this via conda install -y artic-network::rampart=1.0.

Please see the installation docs for further help, including how to install from source or into new conda environments.

More frequent future releases

We hope to release further rampart versions over the coming weeks specifically targeted at improving our ability to sequence SARS-CoV-2. We’ll do this via publishing “release candidate” versions to conda and crowd-sourcing testing via those who are able and willing! Official releases will then be announced here, and we’ll also update the ncov19 repo.

Keep up the good work everyone,
Best,
James Hadfield // ARTIC network

2 Likes
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Please note that if you wish to use live Guppy demultiplexing as the input for the ARTIC bioinformatics pipeline, it is imperative you turn on double barcoding support. This cannot be done via the MinKNOW graphical user interface, but the instructions to do this have been helpfully documented in this thread from Matt Loose.

1 Like
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Is it possible to set rampart to automatically show all the graphs rather than having everything collapsed? It’s a bit of a pain to step through 23 barcodes and open them all (and then switch them globally to depth or reference?).

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Hey Matt – yes there is (the real question is, why isn’t it documented!)

Keyboard shortcuts:
o: open all sample panels
c: close all sample panels
l: switch to log y-scales

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LEGEND!!!

Does need to be documented… the log scale feature is particularly helpful.