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# Scverse Ecosystem Packages
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This repository contains the list of scverse ecosystem packages that are displayed on scverse.org.
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This repository contains the list of scverse ecosystem packages that are displayed on scverse.org and are part of
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the scverse® project.
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The goal is to increase visibility of ecosystem packages and make it easier for users to find appropriate software.
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Registered ecosystem packages can also get their own tag to use on the [scverse forum](https://discourse.scverse.org) for user discussion.
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Authors of these packages can be added the [scverse github organization](https://github.com/scverse).
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Authors of these packages can be added to the [scverse github organization](https://github.com/scverse).
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In the future, we may also test releases of core packages against the test suites of ecosystem packages.
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If a package is part of this list, it means it fulfills certain minimum requirements as outlined below.
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Submit a pull-request adding a `meta.yaml` file for your package to the `packages` directory.
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- Please refer to other entries for examples
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- The full definition of available fields is available in [`schema.json`](schema.json)
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- Please copy the checklist from below into the pull request description and answer all questions.
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- Please copy the checklist from below into the pull request description and answer all questions.
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- Please refer to other entries for examples
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- The full definition of available fields is available in [`schema.json`](scripts/src/ecosystem_scripts/schema.json)
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- You can add a logo in svg/png/webp format if you like. Currently it is not used on our website, though.
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## What are the requirements for an ecosystem package?
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How does the package use scverse data structures (please describe in a few sentences): XXX
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-[ ] The code is publicly available under an [OSI-approved](https://opensource.org/licenses/alphabetical) license
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-[ ] The package provides versioned releases
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-[ ] The package can be installed from a standard registry (e.g. PyPI, conda-forge, bioconda)
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-[ ] Automated tests cover essential functions of the package and a reasonable range of inputs and conditions [^1]
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-[ ] Continuous integration (CI) automatically executes these tests on each push or pull request [^2]
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-[ ] The package provides API documentation via a website or README[^3]
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-[ ] The package uses scverse datastructures where appropriate (i.e. AnnData, MuData or SpatialData and their modality-specific extensions)
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-[ ] I am an author or maintainer of the tool and agree on listing the package on the scverse website
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-[ ] The code is publicly available under an [OSI-approved](https://opensource.org/licenses/alphabetical) license
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-[ ] The package provides versioned releases
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-[ ] The package can be installed from a standard registry (e.g. PyPI, conda-forge, bioconda)
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-[ ] Automated tests cover essential functions of the package and a reasonable range of inputs and conditions [^1]
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-[ ] Continuous integration (CI) automatically executes these tests on each push or pull request [^2]
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-[ ] The package provides API documentation via a website or README[^3]
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-[ ] The package uses scverse datastructures where appropriate (i.e. AnnData, MuData or SpatialData and their modality-specific extensions)
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-[ ] I am an author or maintainer of the tool and agree on listing the package on the scverse website
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### Recommended
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-[ ] Please announce this package on scverse communication channels (zulip, discourse, twitter)
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-[ ] Please tag the author(s) these announcements. Handles (e.g. `@scverse_team`) to include are:
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- Twitter:
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- Zulip:
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- Discourse:
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- Mastodon:
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-[ ] The package provides tutorials (or "vignettes") that help getting users started quickly
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-[ ] The package uses the [scverse cookiecutter template](https://github.com/scverse/cookiecutter-scverse).
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-[ ] Please announce this package on scverse communication channels (zulip, discourse, twitter)
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-[ ] Please tag the author(s) these announcements. Handles (e.g. `@scverse_team`) to include are:
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- Zulip:
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- Discourse:
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- Mastodon:
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- Bluesky:
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- Twitter:
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-[ ] The package provides tutorials (or "vignettes") that help getting users started quickly
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-[ ] The package uses the [scverse cookiecutter template](https://github.com/scverse/cookiecutter-scverse).
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[^1]: We recommend thtat tests cover at least all user facing (public) functions. Minimal tests ensure that the function does not fail on an example data set. Ideally, tests also ensure the correctness of the results, e.g. by comparing against a snapshot.
CellAnnotator is a lightweight tool to query large language models for cell type labels in scRNA-seq data. It can incorporate prior knowledge, and it creates consistent labels across samples in your study.
CellMapper is a leightweight tool to transfer labels, expression values and embeddings from reference to query datasets using k-NN mapping. It's fast and versatile, applicable to mapping scenarios in space, across modalities, or from an atlas to a new query dataset.
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