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Updated: Jan 4, 2026

Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas

Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas

Published on: May 31, 2012

Expression Atlas update: from tissues to single cells.

Irene Papatheodorou¹, Pablo Moreno¹, Jonathan Manning¹

¹European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.

Nucleic Acids Research

|October 31, 2019

Summary

This summary is machine-generated.

Expression Atlas now offers Single Cell Expression Atlas, a resource for gene expression in single cells. Researchers can explore RNA sequencing data across species and cell types to identify marker genes.

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Expression Atlas is a resource for gene and protein expression data.
Single-cell RNA sequencing (scRNA-Seq) datasets are increasingly available.
There is a need for accessible platforms to analyze scRNA-Seq data.

Purpose of the Study:

To extend the Expression Atlas resource with a new service for displaying gene expression in single cells.
To provide an open-access platform for exploring scRNA-Seq data.
To facilitate the identification of marker genes and gene expression patterns in specific cell types.

Main Methods:

Integration of 123 single-cell RNA-Seq studies from 12 species into the Expression Atlas.
Development of a searchable interface by genes, species, tissues, and cell types.
Implementation of t-SNE plots for cell visualization, colored by features or gene expression-based clusters.

Main Results:

The Single Cell Expression Atlas provides access to gene expression data from 123 scRNA-Seq studies.
Users can search for gene expression patterns across species, tissues, and cell types.
Interactive visualization tools allow exploration of gene expression within individual cells and clusters.

Conclusions:

The Single Cell Expression Atlas enhances the Expression Atlas resource by incorporating single-cell resolution gene expression data.
This platform empowers researchers to investigate gene expression dynamics at the single-cell level.
It serves as a valuable tool for discovering marker genes and understanding cellular heterogeneity.