`sourmash` submission

[bluegenes]

Submitting Author: Tessa Pierce-Ward (@bluegenes)
All current maintainers: @ctb, @luizirber, @bluegenes
Package Name: sourmash
One-Line Description of Package: sourmash is a command line tool and Python library for sketching collections of DNA, RNA, and amino acid k-mers for biological sequence search, comparison, and analysis.
Repository Link: https://github.com/sourmash-bio/sourmash
Version submitted: 4.8
Editor: Emily Jane McTavish (@snacktavish)
EiC: @NickleDave
Reviewer 1: Lili Andersson-Li (@LilyAnderssonLee)
Reviewer 2: Elais Player (@elais)
Archive:
Version accepted: v4.8.8
JOSS:
Date accepted (month/day/year): 4/4/2024

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Description

• Include a brief paragraph describing what your package does:

Large collections of genomes, transcriptomes, and raw sequencing data sets are readily available in biology. With the scale of data now available, the field needs lightweight computational methods for searching and summarizing the content of both public and private collections. sourmash implements FracMinHash sketching, a lightweight technique that supports accurate estimation of overlap and containment between two sequencing data sets. sourmash provides a flexible set of programmatic functionality for sequence search and comparison, together with a robust and well-tested command-line interface.

Scope

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  scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

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• Geospatial
• Education
• Pangeo

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

The target audience for sourmash is biologists looking to compare biological sequencing datasets of any kind. sourmash's FracMinHash sketching produces a small, irreversible representation of each dataset, allowing users to search and compare without compromising private data. We provide a user-friendly CLI with mature functionality as well as a python API and experimental Rust API for computational biologists with advanced use cases.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

There are a number of sketching tools for genomic data (e.g. Mash, kmindex, Dashing), each of which implements a slightly different sketching technique. sourmash's FracMinHash enables accurate comparisons of sets of very different sizes (unlike standard MinHash implemented in, e.g. Mash), enabling analysis of genomes contained within metagenomes (Irber et al. 2022), which supports taxonomic profiling (Portik et al., 2022) and content-based search of publicly-available metagenomes. sourmash now additionally supports estimation of Average Nucleotide Identity from FracMinHash (Rahman Hera et al., 2023). The sourmash team has focused on maintaining a robust user interface and continually improving functionality and user experience, with ~ monthly software releases.

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

N/A

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1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[NickleDave]

Thank you @bluegenes for this detailed submission! I am adding initial checks here:

• Installation The package can be installed from a community repository such as PyPI (preferred), and/or a community channel on conda (e.g. conda-forge, bioconda).
  • The package imports properly into a standard Python environment import package-name.
• Fit The package meets criteria for fit and overlap.
• Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
  • User-facing documentation that overviews how to install and start using the package.
  • Short tutorials that help a user understand how to use the package and what it can do for them.
  • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
• Core GitHub repository Files
  • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
  • Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
  • Code of Conduct The package has a Code of Conduct file.
  • License The package has an OSI approved license.
    NOTE: We prefer that you have development instructions in your documentation too.
• Issue Submission Documentation All of the information is filled out in the YAML header of the issue (located at the top of the issue template).
• Automated tests Package has a testing suite and is tested via a Continuous Integration service.
• Repository The repository link resolves correctly.
• Package overlap The package doesn't entirely overlap with the functionality of other packages that have already been submitted to pyOpenSci.
• Archive (JOSS only, may be post-review): The repository DOI resolves correctly.
• Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

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• Initial onboarding survey was filled out
  We appreciate each maintainer of the package filling out this survey individually. 🙌
  Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. 🙌

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[NickleDave]

@bluegenes @ctb @luizirber when you have a chance can all three of you please fill out the pre-survey review linked above?

In the meantime I will proceed with finding an editor 🙂

[snacktavish]

Sorry for the delay! I am signed on a guest editor and will proceed with finding reviewers. Looking forward to checking out your package.

[snacktavish]

I have contacted some reviewers! Hope to have reviewers onboard soon.

[NickleDave]

Awesome, thank you for the updates @snacktavish, we really appreciate you acting as editor for this one. Ok I'll let you take over now 🤐

[snacktavish]

Waiting on responses from reviewers - got some No's, but also some recommendations of possible reviewers. Asking more folks and hoping for some yes's!

[snacktavish]

Emailing some more potential reviewers today! @bluegenes @ctb @luizirber do you have any reviewer suggestions?