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Seed Networks for the Human Cell Atlas
The projects below bring together experimental scientists, computational biologists, software engineers, and physicians to support the continued development of the Human Cell Atlas (HCA), an international effort to map all cells in the human body as a resource for better understanding health and disease.
Showing 38 results
This network will develop a comprehensive, validated atlas of the human kidney at single cell resolution open to the entire scientific and clinical community.
This project will characterize all cell types in the healthy female human reproductive tract using single cell RNA and ATAC sequencing and integrate transcriptomic and epigenetic information.
This network seeks to continue their development and implementation of a multimodal single cell sequencing strategy to determine cellular diversity within the human spinal cord.
This team will analyze single cells and develop computational tools to build a single cell map of the human liver, combining transcriptomics, spatial organization, and cell-cell interactions across diverse individuals and developmental stages.
This project helps build the hematopoietic human cell atlas with single cell transcriptomics, multiplexed spatial imaging data, and a pilot lineage-tracing map in vitro, presented via a portal for exploration and data analysis in the context of the Human Cell Atlas.
The goal of this project is to build a spatially resolved single-cell reference map of the adult human heart.
The goal of this project is to generate an integrated map of cellular diversity in the human immune system across multiple tissues and the human lifespan. It will provide a resource to study mechanisms of tissue residency and the effects of aging.
This network aims to build an atlas of Asian immune cell types and states and characterize differences between six major Asian population groups (Chinese, Japanese, Korean, Indian, Malay, Thai).
This network will define the normal developing and adult human kidney transcriptome and epigenome at cellular resolution, across ages and sex, and benchmark human kidney organoid cell types against this dataset.
This network’s collaborative effort enables the large community of users for the open source software R / Bioconductor to effectively access the Human Cell Atlas for statistical analysis, visualization, and novel scientific discovery.
This team will use single cell and single nucleus RNA-sequencing, computational inference, and histological analysis to generate a comprehensive reference atlas of cell types in the human eye, incorporating data across the natural lifespan.
This project will establish a cell reference atlas of the human neural retina, build a high-resolution spatial map for all cell types in the retina, and develop single cell classification and integrative analysis software tools.
With a goal of understanding how non-coding genetic variation in humans functionally impacts disease traits, this network proposes a framework to map and interpret intra- and inter-individual variation in complex tissues using single cell approaches.
This network will develop an integrated technology to study human cells through a combination of highly multiplexed imaging, classification by deep learning, and ultra-sensitive mass spectrometry-based proteomics.
This network proposes a benchmarking framework to generate guidelines, technologies, quality metrics, and new computational tools that will serve as a compass for the Human Cell Atlas’s generation of reproducible and high-quality tissue atlases.
This project will identify genetic variants that alter the frequency of cell types within human tissues or modulate gene expression or chromatin accessibility within those cell types.
This network’s goal is to generate an African Immune Cell Atlas using single-cell RNA sequencing techniques to profile the transcriptomic and epigenetic profile of peripheral blood mononuclear cells (PBMCs) from ethnically diverse Africans before and after immune stimulation.
This project will establish a comprehensive reference of cell types and cell states in human breast tissue with single cell and spatial resolution.
This network will build a human cell atlas along the gut-brain axis by isolating and profiling vagal nodose ganglion and enteroendocrine cells using single cell RNA-seq and ATAC-seq.
This project will establish a human cell atlas of the female reproductive system, focusing on the ovaries, fallopian tube, and uterus.
This project seeks to establish the normal range of immune phenotypic variability — both within and across individuals — and assess contributions from genetics and environment, such as diurnal, seasonal, and reproductive cycles and life experience.
This network will develop the first version of the Human Lung Cell Atlas by integrating single cell and spatial genomics, microscopy, anatomic, and computational methods.
This network is contributing to an endothelial cell atlas in space and time by mapping the transcriptomes of endothelial cells from several tissues from donors of different ages and ancestry and developing cutting-edge computational tools.
This project will identify inter-individual differences in molecular signatures of human brain cell types, including single cell transcriptomes and DNA methylomes.
This project aims to combine spatially resolved and single cell transcriptional profiling to develop a systematic method for inferring cell-cell interactions, and to apply that method to create a high-resolution spatial atlas of healthy human lymph nodes.
This project brings together scientists with broad and complementary expertise to generate a comprehensive cell atlas of the human thymus across development and aging.
This project’s goal is to map adipose tissue heterogeneity in healthy humans by integrating chemical imaging, single cell, and single nucleus RNA sequencing from adipocytes and adipocyte precursors with distinct anatomical origins and metabolic function.
This network will characterize the single nucleus transcriptomes and intercellular communication networks of human adipose tissue cells (adipocytes and stroma-vascular cells) across fat depots, sex, and ethnicity.
This network will map the human testis in 3D using paired single cell analysis by mass-spectrometry, clampFISH, and RNA-sequencing.
This project will develop a set of generalizable tools, resources, and best practices for multi-modal cell and tissue phenotyping, integrating high-throughput and spatially resolved methods applied to tissues of the human immune system.
This project will investigate the transcriptional and chromatin accessibility landscapes of the human oligodendrocyte lineage during development and in adulthood in both males and females.
This network introduces a novel chromatin profiling technology, CUT&Tag, and will demonstrate its single cell application, thus motivating the development of new experimental and computational tools to transfer their innovation to the global Human Cell Atlas effort and the broader scientific community.
This network will perform single-cell mapping of the normal breast of ethnically diverse populations, including women of African, Latinx, Asian, Ashkenazi Jewish, and Native American descent.
This project will provide the Human Cell Atlas community with datasets, technological advancement, and computational methods for a high-resolution reconstruction of cell lineages and states combining chromatin accessibility and barcoding techniques.
The purpose of this project is to create an atlas of single cell transcriptomic and epigenomic features of the human vasculature to define the cellular composition and key regulatory features of these vessels.
This project will build a spatiotemporal atlas of a single individual’s multi-organ developmental program by applying integrated single-cell RNA-seq and 4i spatial maps to primary tissue and matched iPSC-derived organoids from the same individual.
This project will develop the technology and analytics to sequence pairs of attached tissue cells to determine their interactions and spatial localization. The network will apply these approaches to reconstruct 3D maps and interaction models in the human intestine and bone marrow, studying how cell interactions impact differentiation, proliferation, metabolism, and more.
The Tendon Seed Network will spatially define the transcriptome of extracellular matrix-rich tissues such as tendon across multiple anatomic and micro-anatomic sites. To enable this, the project will develop clinical, laboratory, bioinformatics, and mathematical modelling tools and platforms.
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