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truvari

Structural variant toolkit for VCFs

https://github.com/acenglish/truvari

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 18 committers (11.1%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.3%) to scientific vocabulary

Keywords

annotation-tool benchmarking bioinformatics data-science genomics sequencing structural-variation sv-merging vcf vcf-comparison

Keywords from Contributors

reporting pypi interpretability standardization animal hack autograder
Last synced: 6 months ago · JSON representation

Repository

Structural variant toolkit for VCFs

Basic Info
  • Host: GitHub
  • Owner: ACEnglish
  • License: mit
  • Language: Python
  • Default Branch: develop
  • Homepage:
  • Size: 159 MB
Statistics
  • Stars: 374
  • Watchers: 14
  • Forks: 54
  • Open Issues: 0
  • Releases: 15
Topics
annotation-tool benchmarking bioinformatics data-science genomics sequencing structural-variation sv-merging vcf vcf-comparison
Created almost 8 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

PyPI version pylint FuncTests coverage develop Downloads

Logo
Toolkit for benchmarking, merging, and annotating Structural Variants

📚 WIKI page has detailed user documentation.
🛠️ Developer Docs for the truvari API.
📈 See Updates on new versions.
📝 Read our Papers (#1, #2) to learn more.

💻 Installation

Truvari uses Python 3.6+ and can be installed with pip: python3 -m pip install Truvari For details and more installation options, see Installation on the wiki.

⏩ Quick Start

Each sub-command contains help documentation. Start with truvari -h to see available commands.

The current most common Truvari use case is for structural variation benchmarking: truvari bench -b base.vcf.gz -c comp.vcf.gz -f reference.fa -o output_dir/

Find more matches by harmonizing phased variants using refine: truvari refine output_dir/

Use Truvari's comparison engine to consolidate redundant variants in a merged multi-sample VCF: bcftools merge -m none sampleA.vcf.gz sampleB.vcf.gz | bgzip > merge.vcf.gz tabix merge.vcf.gz truvari collapse -i merge.vcf.gz -o truvari_merge.vcf

🧬 Truvari Commands

  • bench - Performance metrics from comparison of two VCFs
  • collapse - Collapse possibly redundant VCF entries
  • refine - Automated bench result refinement with phab
  • anno - Add SV annotations to a VCF
  • phab - Harmonize variant representations using MSA
  • consistency - Consistency report between multiple VCFs
  • vcf2df - Turn a VCF into a pandas DataFrame
  • segment - Normalization of SVs into disjointed genomic regions
  • stratify - Count variants per-region in vcf
  • divide - Divide a VCF into independent shards
  • ga4gh - Consolidate benchmarking result VCFs

🔎 More Information

All documentation about Truvari is on the WIKI. Additional information about using Truvari can be found in Discussions

Owner

  • Name: Adam English
  • Login: ACEnglish
  • Kind: user

GitHub Events

Total
  • Create event: 11
  • Release event: 4
  • Issues event: 82
  • Watch event: 45
  • Delete event: 10
  • Issue comment event: 139
  • Push event: 159
  • Gollum event: 69
  • Fork event: 4
Last Year
  • Create event: 11
  • Release event: 4
  • Issues event: 82
  • Watch event: 45
  • Delete event: 10
  • Issue comment event: 139
  • Push event: 159
  • Gollum event: 69
  • Fork event: 4

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 1,020
  • Total Committers: 18
  • Avg Commits per committer: 56.667
  • Development Distribution Score (DDS): 0.291
Past Year
  • Commits: 218
  • Committers: 2
  • Avg Commits per committer: 109.0
  • Development Distribution Score (DDS): 0.064
Top Committers
Name Email Commits
Adam English A****h@g****m 723
ACEnglish e****h@s****m 85
Adam English e****s@s****m 77
github-actions[bot] 4****] 66
ACEnglish A****h@f****m 24
ACEnglish a****h@g****m 24
Wen-Wei Liao w****o@w****u 4
Adam English a****7@A****l 3
Boris Noyvert B****t@n****m 3
Rob Flickenger r****b@s****m 3
Aaron Wenger a****r@p****m 1
Caspar Gross m****l@c****e 1
Manuel Bärenz p****g@m****e 1
chapmanb c****b@5****m 1
mohammedkhalfan m****6@n****u 1
pwwang p****g@p****m 1
pwwang 1****g 1
scalavision s****n@g****m 1
Committer Domains (Top 20 + Academic)
spiralgenetics.com: 3 pwwang.com: 1 nyu.edu: 1 50mail.com: 1 manuelbaerenz.de: 1 caspar.one: 1 pacificbiosciences.com: 1 nanoporetech.com: 1 wustl.edu: 1 fabricgenomics.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 179
  • Total pull requests: 18
  • Average time to close issues: 9 days
  • Average time to close pull requests: 6 days
  • Total issue authors: 116
  • Total pull request authors: 10
  • Average comments per issue: 2.41
  • Average comments per pull request: 1.28
  • Merged pull requests: 15
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 33
  • Pull requests: 0
  • Average time to close issues: about 17 hours
  • Average time to close pull requests: N/A
  • Issue authors: 28
  • Pull request authors: 0
  • Average comments per issue: 1.48
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • poddarharsh15 (8)
  • jyw-atgithub (5)
  • TimD1 (5)
  • xiaomiyongyuan (4)
  • shengbing (4)
  • leone93 (4)
  • jiadong324 (4)
  • ACEnglish (4)
  • nate-d-olson (4)
  • vondant (3)
  • johnemajor (3)
  • Han-Cao (3)
  • Flooooooooooooower (3)
  • JoannaTan (3)
  • mnshgl0110 (3)
Pull Request Authors
  • wwliao (5)
  • ctsa (5)
  • pwwang (2)
  • ACEnglish (2)
  • PengJia6 (1)
  • sonny-mo (1)
  • turion (1)
  • scalavision (1)
  • caspargross (1)
  • bnoyvert (1)
Top Labels
Issue Labels
enhancement (5) bug (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 1,468 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 2
  • Total versions: 33
  • Total maintainers: 1
pypi.org: truvari

Structural variant comparison tool for VCFs

  • Versions: 33
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Downloads: 1,468 Last month
Rankings
Stargazers count: 4.2%
Forks count: 6.3%
Average: 8.5%
Dependent packages count: 10.1%
Downloads: 10.6%
Dependent repos count: 11.5%
Maintainers (1)
ACEnglish
Last synced: 6 months ago

Dependencies

.github/workflows/codeql-analysis.yml actions
  • actions/checkout v2 composite
  • github/codeql-action/analyze v1 composite
  • github/codeql-action/autobuild v1 composite
  • github/codeql-action/init v1 composite
.github/workflows/func_tests.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • actions/upload-artifact v3 composite
  • ad-m/github-push-action master composite
.github/workflows/pylint.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • ad-m/github-push-action master composite
.github/workflows/release.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • actions/upload-artifact v2 composite
  • pypa/gh-action-pypi-publish master composite
Dockerfile docker
  • ubuntu 22.04 build
docs/requirements.txt pypi
  • bwapy >=0.1.4
  • edlib >=1.3.8.post2
  • intervaltree >=3.0
  • joblib >=1.0.1
  • numpy >=1.21.2
  • pandas >=1.3.
  • pysam >=0.15.2
  • pytabix >=0.1
  • readthedocs-sphinx-search ==0.1.1
  • sphinx ==4.2.0
  • sphinx_rtd_theme ==1.0.0
setup.py pypi
  • bwapy >=0.1.4
  • edlib >=1.3.9
  • intervaltree >=3.0.2
  • joblib >=1.0.1
  • numpy >=1.23.3
  • pandas >=1.4.4
  • pysam >=0.15.2
  • pytabix >=0.1
  • rich ==12.5.1
pyproject.toml pypi
  • bwapy >=0.1.4
  • edlib >=1.3.9
  • intervaltree >=3.1
  • joblib >=1.2.0
  • numpy >=1.24.4
  • pandas >=1.5.3
  • pyabpoa >=1.4.3
  • pysam >=0.22
  • pytabix >=0.1
  • pywfa >=0.5.1
  • rich >=12.5.1