Filter scRNA-seq cells by mito and gene thresholds and remove doublets.
npx skills add https://github.com/ya-way/cytoclaw-skills --skill sc-adaptive-qc
Please help me install this Agent Skill. Skill: sc-adaptive-qc Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/sc-adaptive-qc Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill sc-adaptive-qc
Adaptive single-cell QC filtering with user-specified mitochondrial and gene thresholds, followed by doublet removal and saving qc_filtered.h5ad.
Run the script with your input path, maximum mitochondrial percent, minimum genes per cell, and an output directory to create qc_filtered.h5ad and a summary.
High-intent search queries and answers about installing and using this skill.
scRNA-seq QC filtering applies user-specified mitochondrial percentage and minimum gene thresholds to raw 10x data, followed by doublet removal to produce a cleaned h5ad file. It reports cell counts before and after filtering.
Scanpy works with Scrublet for optional doublet detection in single-cell RNA-seq data. If Scrublet is unavailable, the Skill uses a safe fallback heuristic to continue removing doublets.
Adaptive single-cell RNA-seq quality control requires setting a maximum mitochondrial percentage and a minimum number of genes per cell. These thresholds filter out low-quality cells before doublet removal.
The best way to remove doublets from raw 10x scRNA-seq data is using threshold-based QC combined with Scrublet detection. This process outputs a qc_filtered.h5ad file and a summary JSON with the doublet rate.
scRNA-seq quality control reports cell counts before and after filtering to track data loss from mitochondrial and gene thresholding, plus doublet removal. It outputs this tracking information in an adaptive_qc_summary.json file.
You can still run adaptive QC if Scrublet fails because the process includes a safe fallback heuristic for doublet detection. This ensures your scRNA-seq data still gets cleaned and exported as qc_filtered.h5ad.
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