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Open AccessJournal ArticleDOI

The Human Cell Atlas

Aviv Regev, +81 more
- 05 Dec 2017 - 
- Vol. 6
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TLDR
An open 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, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract
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. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open 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, and also 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, including a commitment to open data, code, and community.

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Citations
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Journal ArticleDOI

Comprehensive Integration of Single-Cell Data.

TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
Journal ArticleDOI

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Journal ArticleDOI

SCANPY: large-scale single-cell gene expression data analysis

TL;DR: This work presents Scanpy, a scalable toolkit for analyzing single-cell gene expression data that includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks, and AnnData, a generic class for handling annotated data matrices.
Journal ArticleDOI

Fast, sensitive and accurate integration of single-cell data with Harmony.

TL;DR: Harmony, for the integration of single-cell transcriptomic data, identifies broad and fine-grained populations, scales to large datasets, and can integrate sequencing- and imaging-based data.
Journal ArticleDOI

SCENIC: single-cell regulatory network inference and clustering.

TL;DR: On a compendium of single-cell data from tumors and brain, it is demonstrated that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states.
References
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Journal ArticleDOI

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TL;DR: Combinatorial cellular indexing, a strategy for multiplex barcoding of thousands of single cells per experiment, was successfully used to investigate the genome-wide chromatin accessibility landscape in each of over 15,000 single cells, avoiding the need for compartmentalization of individual cells.
Journal ArticleDOI

Optical imaging. Expansion microscopy.

TL;DR: A new approach to image fixed biological samples by expanding the specimen under study reveals mouse brain substructures, and this process can be used to perform scalable superresolution microscopy with diffraction-limited microscopes.
Journal ArticleDOI

A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution

TL;DR: Mutation of a regulatory gene(s) that controls the timing and ratio of symmetric and asymmetric modes of cell divisions in the proliferative zone could create an expanded cortical plate with enhanced capacity for establishing new patterns of connectivity that are validated through natural selection.
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