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Related Experiment Video

Updated: Sep 2, 2025

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Published on: March 14, 2022

Protocol for profiling cell-centric assembled single-cell human transcriptome data in hECA.

Yixin Chen¹, Minsheng Hao¹, Haoxiang Gao¹

¹MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China.

|August 9, 2022

Summary

This summary is machine-generated.

The Human Ensemble Cell Atlas (hECA) offers a unified framework for single-cell transcriptome data. This protocol details hECA applications for cell type annotation and data exploration.

Keywords:

Bioinformatics Computer sciences Gene Expression RNAseq Single Cell

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Last Updated: Sep 2, 2025

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Published on: March 14, 2022

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

Area of Science:

Genomics
Bioinformatics
Cell Biology

Background:

Single-cell RNA sequencing (scRNA-seq) generates vast amounts of data.
Integrating diverse scRNA-seq datasets is crucial for comprehensive human cell analysis.
Existing frameworks often lack unified access and standardized annotation tools.

Purpose of the Study:

To present a protocol for utilizing the Human Ensemble Cell Atlas (hECA).
To demonstrate practical applications of hECA for cell type annotation and data exploration.
To provide a unified informatics framework for large-scale human single-cell transcriptome data.

Main Methods:

Development of the Human Ensemble Cell Atlas (hECA) informatics framework.
Assembly of single-cell transcriptome data from 116 published human cell datasets (1,093,299 cells).
Implementation of three key applications: "quantitative portraiture" exploration, customizable reference creation for annotation, and "in data" cell sorting.

Main Results:

hECA provides access to over a million labeled human cells.
Demonstrated web-based "quantitative portraiture" for data exploration.
Established methods for creating customizable references for automated cell type annotation.
Enabled "in data" cell sorting using logical conditions.

Conclusions:

hECA serves as a valuable resource for unified human single-cell data analysis.
The protocol facilitates efficient cell type annotation of new datasets.
hECA empowers researchers with tools for in-depth exploration and analysis of human cell transcriptomes.