SpyBara
Go Premium

use-cases/scrna-seq-post-count-qc.md 2026-06-09 18:50 UTC to 2026-06-10 20:00 UTC

47 added, 102 removed.

2026
Sat 27 00:02 Thu 25 20:59 Mon 22 19:03 Sat 20 03:58 Fri 19 23:57 Thu 18 23:01 Wed 17 17:02 Tue 16 20:00 Mon 15 19:59 Sun 14 16:58 Sat 13 00:58 Fri 12 18:02 Thu 11 20:02 Wed 10 20:00 Tue 9 18:50 Sat 6 00:58 Fri 5 18:45 Thu 4 01:09 Wed 3 19:27 Tue 2 19:22

name: Annotate scRNA-seq data tagline: Review single-cell QC, annotations, and UMAPs in one thread. summary: Use Codex with the NGS Analysis plugin to turn a 10x-style matrix bundle into QC-filtered single-cell artifacts, threshold-justified filtering summaries, annotations, and UMAPs you can inspect and revise in the same thread. skills:

  • token: NGS Analysis url: codex://plugins/ngs-analysis@openai-curated description: Run single-cell post-count QC and return filtering, visualization, annotation, and notebook artifacts. bestFor:

  • Single-cell teams doing matrix-level QC, annotation, and visualization after count generation.

  • Researchers who need threshold-justified filtering and an auditable record of cells removed or flagged.

  • Teams that want a portable review surface with generated figures, a visualization index, and a notebook or app handoff. starterPrompt: title: Run scRNA-seq Post-count QC body: >- Use the NGS Analysis plugin.

    Route this matrix-level input to scrna-seq-qc using the indicated 10x-style matrix bundle, plus the manifest and dataset metadata.

    Choose QC thresholds from the observed distributions, preserve raw counts, and generate global/per-group UMAPs.

    Return:

    • summary.md

    • a QC summary table with cells removed or flagged per filter

    • threshold-justification plots

    • filtered .h5ad suggestedEffort: high relatedLinks:

  • label: Request access to GPT-Rosalind url: https://openai.com/form/life-sciences-access/

Leverage skills

The NGS Analysis plugin includes:

  • ngs-analysis-router
  • scrna-seq-qc
  • ngs-scrna-seq

When you use the plugin, Codex can use all these packaged skills.

Step-by-step guide

  1. Point Codex to the appropriate matrix, barcodes, genes or features, manifest, and dataset metadata, or provide exact file references.
  2. Run the starter prompt so Codex can choose QC thresholds from the observed distributions and record the rationale in the run artifacts.
  3. Open the visualization index and review notebook or app to inspect QC pass or fail counts, UMAPs, and annotation confidence.
  4. Continue in the same thread to refine thresholds, supply a matched reference atlas, or rerun after unblocking doublet detection.

Results

The run produces a review surface for the filtering decisions, not just a filtered matrix. Begin with the threshold-justification plots and the QC summary so you can see how many cells each filter removed or flagged and whether the selected cutoffs match the observed distributions.

Review threshold-justification plots and QC pass or fail counts for a single-cell run.

Then inspect the generated UMAPs by coarse label and Leiden cluster. These views make it easier to identify annotation gaps, suspicious clusters, or threshold choices that need another pass.

Inspect UMAP plots by coarse label and Leiden cluster.

Finally, review the cell-level metrics and filtering outcomes. Codex preserves this table with the filtered .h5ad and visualization artifacts so you can revise the thresholds in the same thread without losing the rationale for the first pass.

Open cell-level QC metrics and filtering outcomes for review.