StarlitnightlyCommunity·25 Agent Skills Included

omicverse

Complete multi-omics analysis suite for bulk, single-cell, and spatial data

Runs end-to-end genomics workflows covering bulk RNA-seq, single-cell, and spatial transcriptomics analysis. Handles differential expression, cell annotation, trajectory inference, deconvolution, and pathway enrichment without switching tools. Eliminates manual pipeline wiring with ready-made skills, built-in datasets, and AI-agent integration for faster research.

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npx skills add Starlitnightly/omicverse --all -g -y

All Skills in This Repository (25)

Pure Emerald Level Indicators

📦 In Repo

Starlitnightly

STRING protein interaction analysis with omicverse

Query STRING for protein interactions and build styled PPI networks with pyPPI.

Single2Spatial spatial mapping

Convert scRNA-seq references into spatially resolved profiles using Single2Spatial spatial mapping.

Bulk WGCNA analysis with omicverse

Perform bulk WGCNA on expression data to identify gene co-expression modules.

Single-cell annotation skills with omicverse

Predict cell-type labels for scRNA-seq and multimodal single-cell datasets.

Single-cell clustering and batch correction with omicverse

Cluster and batch-correct single-cell AnnData objects with omicverse.

Bulk RNA-seq differential expression with omicverse

Perform bulk RNA-seq differential expression analysis with omicverse.

Single-cell preprocessing with omicverse

Automate single-cell RNA-seq preprocessing with omicverse notebooks for QC, HVG detection, and embeddings.

Spatial transcriptomics tutorials with omicverse

Guide spatial transcriptomics workflows with OmicVerse across preprocessing, deconvolution, and modeling.

Single-cell multi-omics integration

Guide single-cell multi-omics integration workflows with MOFA, GLUE, SIMBA, TOSICA, and StaVIA.

Bulk RNA-seq deconvolution with Bulk2Single

Deconvolve bulk RNA-seq data into synthetic single-cell profiles with beta-VAE.

Bulk RNA-seq DESeq2 analysis with omicverse

Run PyDESeq2 analysis on bulk RNA-seq count matrices with omicverse.

Bulk RNA-seq batch correction with ComBat

Apply ComBat batch correction to merged RNA-seq and microarray expression matrices.

Community

Intermediate

Frequently Asked Questions

FAQPage Schema

How to install omicverse?▼

Run `npx skills add Starlitnightly/omicverse --all -g -y` in your terminal to install all skills in this suite globally.

What can omicverse do for single-cell analysis?▼

It covers the full workflow: QC, normalization, clustering, batch correction, cell type annotation, trajectory inference, and cell-cell communication analysis.

Can omicverse analyze bulk RNA-seq data?▼

Yes. It supports FASTQ-to-count pipelines, DESeq2 differential expression, WGCNA co-expression networks, GSEA enrichment, and TCGA survival analysis.

Does omicverse support spatial transcriptomics?▼

Yes. It handles Visium and Visium HD preprocessing, cell segmentation, deconvolution with Tangram and cell2location, and multi-slice integration.

Can AI agents run omicverse workflows?▼

Yes. OmicVerse provides an MCP server and agent skills so AI assistants like Claude Code can execute analysis steps from plain-English requests.