Metadata-Version: 2.4
Name: spotsweeper
Version: 0.2.2
Summary: Spatially-aware quality control for spatial transcriptomics
Home-page: https://github.com/danielchen05/spotsweeper_py
Author: Daniel Chen
Author-email: xchen274@jh.edu
License: MIT
Project-URL: Documentation, https://pyscaffold.org/
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Requires-Python: >=3.8
Description-Content-Type: text/x-rst; charset=UTF-8
License-File: LICENSE.txt
Requires-Dist: importlib-metadata; python_version < "3.8"
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: anndata
Provides-Extra: testing
Requires-Dist: setuptools; extra == "testing"
Requires-Dist: pytest; extra == "testing"
Requires-Dist: pytest-cov; extra == "testing"
Dynamic: license-file

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==============
SpotSweeper
==============


    Spatially-aware quality control for spatial transcriptomics


SpotSweeper is a package developed for spatially-aware quality control (QC) methods for the detection, visualization, and removal of both local outliers and regional artifacts in spot-based spatial transcriptomics data, such as 10x Genomics Visium, using standard QC metrics.

Features
--------
- Detect local outliers using robust z-score
- Plot and highlight local outliers in a spatial context (both showing on screen (interactive) and saving to PDF)

Installation
------------

Install from PyPI:

.. code-block:: bash

    pip install spotsweeper

Usage
-----

.. code-block:: python

    import spotsweeper.local_outliers as lo 
    import spotsweeper.plot_QC as plot_QC
    import spotsweeper.plot_QCpdf as pdf
    lo.local_outliers(adata, metric = "total_counts", sample_key = "region")
    plot_QC.plot_qc_metrics(adata,"region",metric = "total_counts", outliers="total_counts_outliers")
    pdf.plot_qc_pdf(adata,"region",metric = "total_counts", outliers="total_counts_outliers")

Project Status
--------------

This package is in early development. Use with caution; interfaces may change. 

.. _pyscaffold-notes:

Note
====

This project has been set up using PyScaffold 4.6. For details and usage
information on PyScaffold see https://pyscaffold.org/.
