spotsweeper 0.1.3

Spatially-aware quality control for spatial transcriptomics

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

Installation

Install from PyPI:

pip install spotsweeper

Usage

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. 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/.