instrain

Bioinformatics program inStrain

https://github.com/mrolm/instrain

Science Score: 59.0%

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 3 DOI reference(s) in README
  • Academic publication links
    Links to: biorxiv.org
  • Committers with academic emails
    8 of 17 committers (47.1%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (6.8%) to scientific vocabulary

Keywords from Contributors

assembly bioinformatics metagenomics microbial-genomes microbiology
Last synced: 6 months ago · JSON representation

Repository

Bioinformatics program inStrain

Basic Info
  • Host: GitHub
  • Owner: MrOlm
  • License: mit
  • Language: Python
  • Default Branch: master
  • Size: 261 MB
Statistics
  • Stars: 168
  • Watchers: 6
  • Forks: 36
  • Open Issues: 12
  • Releases: 1
Created over 6 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License

README.md

inStrain

Downloads Downloads

inStrain is a python program for analysis of co-occurring genome populations from metagenomes that allows highly accurate genome comparisons, analysis of coverage, microdiversity, and linkage, and sensitive SNP detection with gene localization and synonymous non-synonymous identification.

Manual, installation instructions, and expected output are at available at ReadTheDocs

Publication is available in Nature Biotechnology and on bioRxiv

Installation options

pip

$ pip install instrain

bioconda

$ conda install -c conda-forge -c bioconda -c defaults instrain

Docker

Docker image is available on Docker Hub at mattolm/instrain. See docker/ for use instructions.

Quick start

Show program help and modules:

$ inStrain -h

Microdiversity and SNP-calling pipeline:

$ inStrain profile mapping.bam genome_file.fasta -o inStrain_profile1

Detailed strain-level comparison:

$ inStrain compare inStrain_profile1 inStrain_profile2

Owner

  • Name: Matt Olm
  • Login: MrOlm
  • Kind: user
  • Location: San Francisco, CA
  • Company: Stanford University

Postdoc in Justin Sonnenburg's lab at Stanford

GitHub Events

Total
  • Issues event: 55
  • Watch event: 31
  • Issue comment event: 57
  • Push event: 5
  • Fork event: 3
  • Create event: 1
Last Year
  • Issues event: 55
  • Watch event: 31
  • Issue comment event: 57
  • Push event: 5
  • Fork event: 3
  • Create event: 1

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 273
  • Total Committers: 17
  • Avg Commits per committer: 16.059
  • Development Distribution Score (DDS): 0.425
Past Year
  • Commits: 9
  • Committers: 1
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Matt Olm m****m@g****m 157
Matt Olm m****m@M****l 54
Alex Crits-Christoph a****1@j****u 18
Matt Olm m****m@M****l 15
Matt Olm m****m@M****l 11
Matt Olm m****m@s****u 3
Matt Olm m****m@m****u 3
Jing Wang z****e@s****n 2
Matt Olm m****m@D****t 2
Matt Olm m****m@b****u 1
Matt Olm m****m@s****u 1
Matt Olm m****m@u****u 1
szimmerman92 s****n@g****m 1
rusher321 r****i@g****n 1
Vini Salazar 1****r 1
Mike Lee m****7@g****m 1
Francisco Zorrilla f****4@c****k 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 155
  • Total pull requests: 7
  • Average time to close issues: 2 months
  • Average time to close pull requests: 1 day
  • Total issue authors: 99
  • Total pull request authors: 7
  • Average comments per issue: 3.69
  • Average comments per pull request: 1.43
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 21
  • Pull requests: 0
  • Average time to close issues: 19 days
  • Average time to close pull requests: N/A
  • Issue authors: 18
  • Pull request authors: 0
  • Average comments per issue: 1.29
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • gabrieleghiotto (5)
  • ChenTianYi99 (5)
  • liamfitzstevens (5)
  • haihao999 (4)
  • jmartin77777 (4)
  • zhaoc1 (4)
  • mcmahon-uw (3)
  • jdwinkler-lanzatech (3)
  • kirkgrubbs1 (3)
  • rrohwer (3)
  • 473021677 (3)
  • rebeccasophiasalcedo (3)
  • Thexiyang (3)
  • DDavila10 (3)
  • szimmerman92 (2)
Pull Request Authors
  • zhenjiaofenjie (2)
  • alexcritschristoph (1)
  • nick-youngblut (1)
  • rusher321 (1)
  • vinisalazar (1)
  • szimmerman92 (1)
  • franciscozorrilla (1)
Top Labels
Issue Labels
enhancement (9) bug (3) documentation (3) good first issue (2) system specific bug (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 56 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 65
  • Total maintainers: 2
pypi.org: instrain

Calculation of strain-level metrics

  • Versions: 63
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 56 Last month
Rankings
Stargazers count: 6.8%
Forks count: 7.1%
Dependent packages count: 10.0%
Average: 14.3%
Dependent repos count: 21.7%
Downloads: 25.9%
Maintainers (1)
Last synced: 6 months ago
spack.io: py-instrain

inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly accurate genome comparisons, analysis of coverage, microdiversity, and linkage, and sensitive SNP detection with gene localization and synonymous non- synonymous identification.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Stargazers count: 19.3%
Forks count: 20.3%
Average: 24.2%
Dependent packages count: 57.3%
Maintainers (1)
Last synced: 7 months ago

Dependencies

setup.py pypi
  • biopython <=1.74
  • h5py *
  • lmfit *
  • matplotlib *
  • networkx *
  • numba *
  • numpy *
  • pandas >=0.25,
  • psutil *
  • pysam >=0.15
  • pytest *
  • scikit-learn *
  • seaborn *
  • tqdm *
docker/Dockerfile docker
  • continuumio/miniconda3 4.6.14 build
test/docker_tests/accessible_test_data/Dockerfile docker
  • continuumio/miniconda3 latest build