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https://github.com/brisvag/waretomo

Overengineered batch processing script for tomography data with Warp and aretomo.

https://github.com/brisvag/waretomo

Science Score: 49.0%

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    Found 1 DOI reference(s) in README
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    Links to: zenodo.org
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    Scientific vocabulary similarity
    Low similarity (15.8%) to scientific vocabulary

Keywords from Contributors

projection interactive archival generic sequences observability autograding hacking shellcodes modular
Last synced: 7 months ago · JSON representation

Repository

Overengineered batch processing script for tomography data with Warp and aretomo.

Basic Info
  • Host: GitHub
  • Owner: brisvag
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 55.7 KB
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 6
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

waretomo

License PyPI DOI Python Version CI codecov

Overengineered batch processing script for tomography data with Warp and AreTomo.

NOTE: This was tested with AreTomo 1.3.4, i's recommended to use the same version.

Installation and usage

bash pip install waretomo

bash waretomo -h

Every time you run waretomo, a log will be appended to an waretomo.log file in the output directory.

Walkthrough

Here's a short summary of how I recommend using this script:

  • pre-process your dataset in Warp, up to Create stack for imod. Make sure to deselect bad tilts from the warp interface; they will be skipped in subsequent steps
  • run waretomo in dry-run mode (-d), to make sure everything is set up correctly. Pass any other options you'd like (see waretomo -h for a complete list and shorthands): bash waretomo . --mdoc-dir ./mdocs -b 8 -t 800 -d
  • follow error messages if any arise (you may have to provide the path to the AreTomo executable with --aretomo, for example)
  • once the above command works, it will give you a summary of inputs and of the upcoming pipeline. It's time to try to run it on a single tomogram, using -j (--just). Note that the name to provide to -j is the tomogram name given at the top of the mdoc file (ImageFile = <something>), and not the input file (this is because warp actually uses this value for all subsequent outputs). bash waretomo . --mdoc-dir ./mdocs -b 8 -t 800 -j tiltseries_23.mrc
  • this will run the full pipeline on that tomogram. Keep an eye out for error messages, they might give you tips for solving them.
  • if everything works, you will now have a few outputs to check out:
    • ./waretomo_processing/tiltseries_23.mrc: raw aretomo reconstruction.
    • ./waretomo_processing/denoised/tiltseries_23.mrc: same as above, denoised with topaz for better annotation
    • <mdoc-dir>/mdoc_tilted/tiltseries_23.mrc.mdoc: mdoc file updated with skipped tilt and with adjusted tilt angles from aretomo's TiltAlign option (e.g: to align lamellae to the XY plane)
    • ./waretomo_processing/tiltseries_23.xf: alignment metadata, used by warp together with above mdocs for reconstruction.
  • check out the reconstructions and make sure everything looks as you want. If anything is wrong, adjust parameters as you see fit. You can also run only parts of the script by using the --start-from and --stop-at options (both are inclusive). Use -f if you want to overwrite existing outputs.
  • once you're happy, remove the -j option to process the full dataset.

At this point, you're ready to go back to Warp. Here, you can simply import tilt series from IMOD. Don't forget to provide the mdoc_tilted directory instead of the original mdocs. Set waretomo_processing as the Root folder with IMOD processing results, and Warp will find the xf files located there. Provide the pixel size of the binned aretomo reconstructions (find out with e.g: header waretomo_processing/tiltseries_23.mrc.mrc). You might have to provide the dose per tilt, depending on the origin/correctness of your mdocs.

You can now proceed with reconstructing with Warp, use M, and so on, while having matching AreTomo reconstructions with their local patch alignments and subsequent denoising to maximize readability for picking and annotation.

Owner

  • Name: Lorenzo Gaifas
  • Login: brisvag
  • Kind: user
  • Company: @gutsche-lab

PhD student at @gutsche-lab, doing computational stuff with cryo-ET data.

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 2
  • Pull request event: 2
  • Create event: 3
Last Year
  • Issues event: 1
  • Watch event: 1
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 2
  • Pull request event: 2
  • Create event: 3

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 35
  • Total Committers: 2
  • Avg Commits per committer: 17.5
  • Development Distribution Score (DDS): 0.143
Past Year
  • Commits: 3
  • Committers: 2
  • Avg Commits per committer: 1.5
  • Development Distribution Score (DDS): 0.333
Top Committers
Name Email Commits
Lorenzo Gaifas b****g@g****m 30
dependabot[bot] 4****] 5

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 1
  • Total pull requests: 5
  • Average time to close issues: N/A
  • Average time to close pull requests: about 21 hours
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 5
Past Year
  • Issues: 1
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 day
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 1
View more stats
Top Authors
Issue Authors
  • lmcarreira (1)
Pull Request Authors
  • dependabot[bot] (8)
Top Labels
Issue Labels
Pull Request Labels
dependencies (8)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 18 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
pypi.org: waretomo

Overengineered batch processing script for tomography data with Warp and aretomo.

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 18 Last month
Rankings
Dependent packages count: 7.5%
Average: 38.7%
Dependent repos count: 69.9%
Maintainers (1)
brisvag
Last synced: 8 months ago

Dependencies

.github/workflows/ci.yml actions
  • JasonEtco/create-an-issue v2 composite
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
  • codecov/codecov-action v3 composite
  • softprops/action-gh-release v1 composite
pyproject.toml pypi
  • GPUtil *
  • click *
  • mdocfile ==0.1.0
  • pandas *
  • rich *
  • sh *
  • topaz-em ==0.2.5