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Pynteny: a Python package to perform synteny-aware, profile HMM-based searches in sequence databases #67

@Robaina

Description

@Robaina

Submitting Author: Semidán Robaina (@Robaina)
All current maintainers: @Robaina
Package Name: Pynteny
One-Line Description of Package: Query sequence database by HMMs arranged in predefined synteny structure
Repository Link: https://github.com/Robaina/Pynteny
Version submitted: v0.0.5
Editor: @arianesasso
Reviewer 1: @Batalex
Reviewer 2: @c-thoben
Archive: DOI
JOSS DOI: DOI
Version accepted: 1.0.0
Date accepted (month-day-year): 03-10-2023


Description

  • Include a brief paragraph describing what your package does:j

Pynteny is Python tool to search for synteny blocks in (prokaryotic) sequence data through HMMs of the ORFs of interest and HMMER. By leveraging genomic context information, Pynteny can be employed to decrease the uncertainty of functional annotation of unlabelled sequence data due to the effect of paralogs. Pynteny can be accessed (i) through the command line, (ii) as a Python module, or (iii) as a (locally served) web application.

Scope

  • Please indicate which category or categories this package falls under:
    • Data retrieval
    • Data extraction
    • Data munging
    • Data deposition
    • Data visualization
    • Reproducibility
    • Geospatial
    • Education
    • Unsure/Other (explain below)

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  • Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

Pynteny's main objective is to provide a means to query NGS (unannotated) sequence databases, such as metagenomic/metatranscriptomic datasets using syntenic blocks (i.e. spatial arrangements of genes) rather than single target genes/protein domains. In this sense, I would classify Pynteny within Data Extraction.

  • Who is the target audience, and what are the scientific applications of this package?

Pynteny was designed to be used by researchers working with large, unannotated sequence databases, such as those typically encountered in metagenomic analyses. It can be accessed through a command line interface or easily integrated into pipelines as a Python package. Pynteny can also be used through a graphical interface running locally in the browser, which is more suitable for educational purposes.

  • Are there other Python packages that accomplish similar things? If so, how does yours differ?

To the extent of my knowledge, there isn't any Python package that provides the functionality provided by Pynteny.

Technical checks

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  • does not violate the Terms of Service of any service it interacts with.
  • has an OSI approved license.
  • contains a README with instructions for installing the development version.
  • includes documentation with examples for all functions.
  • contains a vignette with examples of its essential functions and uses.
  • has a test suite.
  • has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others: GitHub Action

Publication options

I had submitted this package for publication at JOSS prior to pyOpenSci. The submission is currently under consideration for scope in this issue: openjournals/joss-reviews#4978

JOSS Checks
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  • The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI: DOI

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