single-cell-clustering-and-batch-correction-with-omicverse

name	single-cell-clustering-and-batch-correction-with-omicverse
title	Single-cell clustering and batch correction with omicverse
description	Guide Claude through omicverse's single-cell clustering workflow, covering preprocessing, QC, multimethod clustering, topic modeling, cNMF, and cross-batch integration as demonstrated in t_cluster.ipynb and t_single_batch.ipynb.

Single-cell clustering and batch correction with omicverse

Overview

This skill distills the single-cell tutorials t_cluster.ipynb and t_single_batch.ipynb. Use it when a user wants to preprocess an AnnData object, explore clustering alternatives (Leiden, Louvain, scICE, GMM, topic/cNMF models), and evaluate or harmonise batches with omicverse utilities.

Instructions

1. Import libraries and set plotting defaults
   • Load omicverse as ov, scanpy as sc, and plotting helpers (scvelo as scv when using dentate gyrus demo data).
   • Apply ov.plot_set() or ov.utils.ov_plot_set() so figures adopt omicverse styling before embedding plots.
2. Load data and annotate batches
   • For demo clustering, fetch scv.datasets.dentategyrus(); for integration, read provided .h5ad files via ov.read() and set adata.obs['batch'] identifiers for each cohort.