single-cell-rna-qc

What problem does it solve?

This Skill automates the critical quality control (QC) process for single-cell RNA-seq data, ensuring that only high-quality cells and genes are used for downstream analysis, thereby improving the reliability of research findings.

Core Features & Use Cases

• Automated QC Pipeline: Runs a comprehensive QC workflow using scverse best practices, including calculating metrics, filtering low-quality cells, and generating visualizations.
• MAD-Based Filtering: Employs robust Median Absolute Deviation (MAD) methods for outlier detection, adapting to dataset-specific variations.
• Flexible Approaches: Offers a complete pipeline script for standard use and modular functions for custom analysis workflows.
• Use Case: A researcher has generated single-cell RNA-seq data and needs to filter out dead cells, empty droplets, and genes with low detection rates before proceeding to clustering and cell type annotation. This Skill provides an automated and best-practice-compliant solution.

Quick Start

Use the single-cell rna qc skill to perform a complete quality control pipeline on the file 'my_data.h5ad'.