The Human Cell Atlas

By Aviv Regev, Sara A Teichmann, Eric S. Lander, Ido Amit, C. Benoist, Ewan Birney, B. Bodenmiller, Peter Campbell, P. Carninci, M. Clatworthy and 51 more. 2017

1,788 citations recorded by the source corpus.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body, by undertaking a Human Cell Atlas Project as an international collaborative effort. The aim would be to define all human cell types in terms of distinctive molecular profiles (e.g., gene expression) and connect this information with classical cellular descriptions (e.g., location and morphology). A comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, as well as provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas.

Subfields: Biophysics, Molecular Biology, Oncology

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Citations in the corpus

Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis (2019, methodology): “The analyses and annotations of cell types presented here are not exhaustive, and will likely be improved in the future, particularly with the help of computational tools developed by research consortia, such as Human Cell Atlas (60).”
Characterization of cell fate probabilities in single-cell data with Palantir (2019, neutral): “We anticipate that Palantir will be a valuable discovery tool for many less characterized systems, including those profiled by the Human Cell Atlas Project 43 .”
Dictionary learning for integrative, multimodal, and massively scalable single-cell analysis (2022, neutral): “During the coronavirus disease 2019 (COVID-19) pandemic, there has been widespread scRNA-seq data collection from respiratory tissues, particularly by the Human Cell Atlas Lung Biological Network 57 .”
A test metric for assessing single-cell RNA-seq batch correction (2018, neutral): “We expect this discussion to have serious repercussions for decisions regarding experimental design in emerging single-cell expression atlases such as the Human Cell Atlas 39 and the Mouse Cell Atlas 40 .”
The protein expression profile of ACE2 in human tissues (2020, neutral): “The largest initiative aiming to create a comprehensive map of human organs based on scRNA-seq is the Human Cell Atlas consortium, which coordinates efforts from > 1,000 different institutes across > 70 countries (Regev et al , 2017).”
Artificial Intelligence in Cancer Research and Precision Medicine (2021, neutral): “Nonetheless, these gaps are being addressed, from using higher-throughput solutions for scRNA-seq (such as 10 × Chromium) to coordinating global initiatives such as The Human Cell Atlas that aim to comprehensively profile every cell type of the human body (63).”
Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks (2018, background): “A recently proposed idea of building a reference map of all human cell types based on high-throughput single-cell experiments (called the Human Cell Atlas [Regev et al., 2017]) is closely related to our vision.”