AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs)…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Spatial epigenomics analysis: spatially resolved chromatin accessibility and gene regulation.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/spatial-epigenomics-agent
Skill Snapshot
Source Doc
Spatial ATAC Analysis: Process spatial chromatin accessibility data to identify open chromatin regions with spatial coordinates.
Spatial CUT&Tag: Analyze spatially-resolved histone modification profiles (H3K27ac for enhancers, H3K4me3 for promoters).
Spatial Methylation: Map DNA methylation patterns across tissue sections using spatial bisulfite methods.
Multi-Modal Integration: Combine spatial epigenomics with spatial transcriptomics for regulatory network inference.
Regulatory Element Mapping: Identify spatially-variable enhancers, promoters, and silencers.
3D Chromatin Organization: Integrate with MERFISH/seqFISH+ for spatial chromatin organization.
| Technology | Epigenetic Mark | Resolution | Method |
|---|---|---|---|
| Spatial-ATAC-seq | Open chromatin | ~10-50μm | Microfluidic barcoding |
| DBiT-seq | ATAC + expression | ~10μm | Deterministic barcoding |
| Spatial-CUT&Tag | Histone marks | ~50μm | Cleavage under targets |
| Spatial-MethylSeq | DNA methylation | Variable | Bisulfite conversion |
| MERFISH + epigenetics | 3D organization | Single-cell | Imaging-based |
Input: Spatial epigenomics data (BAM files + spatial coordinates) or processed peak matrices.
Preprocessing: Alignment, deduplication, peak calling with spatial awareness.
Spatial Clustering: Identify spatial domains with similar epigenetic profiles.
Peak Annotation: Map peaks to genomic features (promoters, enhancers, gene bodies).
Motif Analysis: Identify transcription factor binding motifs in spatially-variable peaks.
Integration: Combine with expression data for regulatory inference.
Output: Spatial peak maps, regulatory networks, domain annotations.
Related skills
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs)…
Arboreto is a computational library for inferring gene regulatory networks (GRNs) from gene expression data using paralleli.
Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cel…
Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and ac…