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omicverse-single-cell-kb-alignment

Build kb references and quantify scRNA-seq FASTQs into count matrices with OmicVerse alignment wrappers.

13|2|Updated Apr 5, 2026
Search Tags:#workflow#reference#alignment#single-cell#omics#counting
One-click install
npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-kb-alignment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: omicverse-single-cell-kb-alignment
Source: https://github.com/Starlitnightly/omicverse-skills/tree/main/src/omicverse_skills/skills/single-cell-kb-alignment
Command: npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-kb-alignment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a repeatable way to build a kb reference from FASTA/GTF inputs and quantify single-cell FASTQs into count matrices using OmicVerse alignment wrappers, stopping at the count stage to keep downstream QC/preprocessing separate.

Core Features & Use Cases

  • Build a kb reference: generate index and t2g mappings from fasta/gtf data.
  • Count cells: quantify reads into count matrices with ov.alignment.single.count, producing outputs ready for downstream analysis.
  • Flexible workflows: supports standard and nucleus modes and aligns with downstream preprocessing pipelines for single-cell RNA-seq.

Quick Start

Install the skill, then build the reference with ov.alignment.single.ref(...) and run ov.alignment.single.count(...) on your FASTQs.

Frequently Asked Questions about omicverse-single-cell-kb-alignment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a kb reference from FASTA and GTF files for scRNA-seq counting?▼

You can build a kb reference from FASTA and GTF files by using the ov.alignment.single.ref wrapper, which generates the necessary index and t2g mappings for single-cell RNA-seq read quantification.

What's the best way to turn scRNA-seq FASTQ data into count matrices?▼

To turn scRNA-seq FASTQ data into count matrices, build a kb reference with ov.alignment.single.ref and then run ov.alignment.single.count on matching FASTQ files to produce ready-to-use outputs.

Does this scRNA-seq alignment workflow support nucleus mode?▼

Yes, this scRNA-seq alignment workflow supports both standard and nucleus modes, providing flexible read counting options to align with downstream preprocessing pipelines.

Can I load the count matrix output directly for downstream QC and preprocessing?▼

Yes, you can load the output by optionally loading adata.h5ad for downstream steps, as the workflow explicitly stops at the count stage to keep QC and preprocessing separate.

Why does my single-cell count matrix workflow stop before quality control?▼

The workflow stops at the count stage to intentionally keep downstream QC and preprocessing separate, ensuring the count matrix output remains modular for subsequent pipelines.

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