Spatially-aware quality control for spatial transcriptomics
Project description
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
(to be added) Plotting functions of local outliers
Installation
Install from PyPI:
pip install spotsweeperUsage
import spotsweeper.local_outliers as lo
lo.local_outliers(adata, metric = "total_counts", sample_key = "region")Project Status
This package is in early development. Use with caution; interfaces may change. Tests haven’t been implemented and will be added in a future version.
Note
This project has been set up using PyScaffold 4.6. For details and usage information on PyScaffold see https://pyscaffold.org/.
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