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Merge pull request #24 from quadbio/feature/docs
Update the README
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README.md

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[![Coverage][badge-coverage]][coverage]
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[![Documentation][badge-docs]][documentation]
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[![Pre-commit.ci][badge-pre-commit]][pre-commit]
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[![PyPI][badge-pypi]][pypi]
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[badge-tests]: https://img.shields.io/github/actions/workflow/status/quadbio/cell-annotator/test.yaml?branch=main
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[badge-coverage]: https://codecov.io/gh/quadbio/cell-annotator/branch/main/graph/badge.svg
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[badge-docs]: https://img.shields.io/readthedocs/cell-annotator
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[badge-pre-commit]: https://results.pre-commit.ci/badge/github/quadbio/cell-annotator/main.svg
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[badge-pypi]: https://img.shields.io/pypi/v/cell-annotator.svg
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A tool to annotate cell types in scRNA-seq data based on marker genes using OpenAI models.
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- Retrieve reliable results thanks to [OpenAI structured outputs](https://platform.openai.com/docs/guides/structured-outputs)
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- Use this tool to quickly generate pre-integration cell type labels to either score your integration quality (e.g. [scIB metrics](https://scib-metrics.readthedocs.io/en/stable/)) or to guide your integration effort (e.g. [scPoli](https://docs.scarches.org/en/latest/), [scANVI](https://docs.scvi-tools.org/en/stable/api/reference/scvi.model.SCANVI.html)).
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Note that this package is based on output generated by large language models and might **sometimes make mistakes**. We use some safeguards, like anchoring the tool in a multi-step process, and using structured output predictions, but mistakes are still possible. We recommend using this tool as a first step in an annotation workflow to generate an initial, coarse set of annotations that must be further refined.
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## Installation
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You need to have Python 3.10 or newer installed on your system.
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[coverage]: https://codecov.io/gh/quadbio/cell-annotator
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[documentation]: https://cell-annotator.readthedocs.io
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[pre-commit]: https://results.pre-commit.ci/latest/github/quadbio/cell-annotator/main
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[pypi]: https://pypi.org/project/cell-annotator/

docs/conf.py

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info = metadata("cell-annotator")
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project_name = info["Name"]
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author = info["Author"]
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copyright = f"{datetime.now():%Y}, {author}."
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copyright = f"{datetime.now():%Y}, QuaDBio Lab."
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version = info["Version"]
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urls = dict(pu.split(", ") for pu in info.get_all("Project-URL"))
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repository_url = urls["Source"]

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