skills.rest
Starlitnightly
StarlitnightlyCOMMUNITY
Explore all skills by this author →
GitHub

omicverse-single-cell-differential-expression

Compare conditions per cell type in AnnData with Wilcoxon, t-test, or memento backends.

13|2|Updated Apr 5, 2026
Search Tags:#bioinformatics#single-cell#anndata#differential-expression#deg#wilcoxon#memento-de
One-click install
npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-differential-expression
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: omicverse-single-cell-differential-expression
Source: https://github.com/Starlitnightly/omicverse-skills/tree/main/src/omicverse_skills/skills/single-cell-differential-expression
Command: npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-differential-expression

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, anndata, omicverse, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Turn interactive notebook DEG workflows into a repeatable, triggerable analysis that compares conditions inside one or more cell types in an AnnData object, removing guesswork about backend choice, matrix provenance, and result validation.

Core Features & Use Cases

  • Subset AnnData by cell-type and condition, then run differential expression using Wilcoxon, t-test, or memento-de backends.
  • Auto-detect and prefer raw counts from adata.raw or a counts layer, attempt count recovery when appropriate, and downsample large subsets via max_cells.
  • Produce standardized DEG tables augmented with log2FC, pvalue, padj, baseMean, pct_ctrl, pct_test, and pct_diff for downstream plotting and reporting.
  • Use Case: compare Control vs Salmonella within a specific epithelial subpopulation, verify result columns, and optionally rerun with memento-de for count-aware inference.

Quick Start

Run a per-cell-type differential expression comparing Control and Salmonella inside an AnnData object using the wilcoxon backend and default validation checks.

Frequently Asked Questions about omicverse-single-cell-differential-expression

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

FAQPage Schema
How do I run single-cell differential expression across conditions within specific cell types?▼

Single-cell differential expression compares conditions inside specific cell types by subsetting AnnData with cell-type and condition annotations, then applying Wilcoxon, t-test, or memento backends to generate standardized DEG tables.

What is the best way to handle raw counts for single-cell DEG analysis in AnnData?▼

Handling raw counts for single-cell DEG analysis involves auto-detecting and preferring counts from adata.raw or a counts layer, attempting count recovery when appropriate, and enforcing max_cells downsampling for large subsets.

Can I use memento for count-aware differential expression on anndata objects?▼

You can use memento-de as a backend for count-aware inference on anndata objects, providing an alternative to Wilcoxon or t-test backends when comparing conditions within specific cell populations.

What columns are included in the differential expression result tables?▼

Differential expression result tables include log2FC, pvalue, padj, baseMean, pct_ctrl, pct_test, and pct_diff columns, designed for downstream plotting and reporting of per-cell-type comparisons.

Does single-cell DEG analysis require pre-annotated cell types and conditions?▼

Single-cell DEG analysis requires AnnData objects with both condition and cell-type annotations to perform per-cell-type comparisons, ensuring the workflow can accurately subset data and compare relevant populations.

Why does my single-cell differential expression workflow fail on large cell subsets?▼

Single-cell differential expression workflows on large cell subsets require max_cells downsampling to manage computational load, subset by cell type, and verify result columns effectively.

Related Skills

Explore More Education & Research Skills→
omicverseomicverse
13

omicverse-single-cell-differential-expression

Run single-cell differential expression analysis on AnnData datasets with Wilcoxon, t-test, or memento-de workflows.

Official
Advanced
TTAWDTTTTAWDTT
5

scientific-visualization

Generate publication-ready scientific figures with matplotlib, seaborn, and plotly.

Community
Advanced
pwwangpwwang
22

pseudobulkdeg

Aggregate single-cell counts into pseudo-bulk samples and test differential expression with DESeq2 or edgeR.

Community
Advanced
omicverseomicverse
32

bulk-rna-seq-differential-expression-with-omicverse

Analyze bulk RNA-seq count matrices for differential expression and pathway enrichment.

Official
Advanced