single-cell-encode

What problem does it solve?

This Skill enables users to discover, interpret, and analyze ENCODE's single-cell genomics datasets, facilitating understanding of cell-type-specific regulation and heterogeneity.

Core Features & Use Cases

• Dataset Discovery: Search for ENCODE single-cell experiments such as scRNA-seq and scATAC-seq across tissues and platforms.
• Data Retrieval: List and access raw and processed data files, including gene expression matrices and chromatin accessibility profiles.
• Data Integration and Analysis: Guide integration of single-cell data within ENCODE or with external atlases, performing cross-study comparisons, and validating signals with bulk data.
• Use Case: Identify ENCODE scRNA-seq datasets for pancreas, obtain their expression matrices, and compare cell-type markers with bulk datasets to interpret regulatory landscapes.

Quick Start

Search for ENCODE scRNA-seq experiments in a tissue of interest and retrieve associated data files to begin analysis.