Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging

Quardokus, Ellen M.; Saunders, Diane; McDonough, Elizabeth; Hickey, John W.; Werlein, Christopher; Surrette, Christine; Rajbhandari, Presha; Casals, Anna Martinez; Tian, Hua; Lowery, Lisa; Neumann, Elizabeth K.; Björklund, Frida; Neelakantan, Taruna V.; Croteau, Joshua; Wiblin, Anne E.; Fisher, Jeremy; Livengood, April J.; Dowell, Karen G.; Silverstein, Jonathan C.; Spraggins, Jeffrey M.; Pryhuber, Gloria S.; Deutsch, Gail H.; Ginty, Fiona; Nolan, Garry P.; Melov, Simon; Jonigk, Danny; Caldwell, Michael; Vlachos, Ioannis S.; Müller, Werner; Gehlenborg, Nils; Stockwell, Brent R.; Lundberg, Emma; Snyder, M; Germain, Ronald N.; Camarillo, Jeannie M.; Kelleher, Neil L.; Börner, Katy; Radtke, Andrea J.

doi:10.1038/s41592-023-01846-7

Cited by 17 publications

(3 citation statements)

References 25 publications

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“…As of May 2023, Azimuth references exist for ten healthy human organs that can be explored using Vitessce 28 ; these references have been used to automatically annotate approximately 280 million cells in about 20,000 datasets. For seven organs, standardized Organ Mapping Antibody Panels (https://humanatlas.io/omap) have been established that make it possible to map new experimental data to the evolving atlas 5 .…”

Section: Perspectivementioning

confidence: 99%

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

et al. 2023

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The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.HuBMAP was founded with the goal of establishing state-of-the-art frameworks for building spatial multiomic maps of non-diseased human organs at single-cell resolution 1 . During the first phase (2018)(2019)(2020)(2021)(2022), the priorities of the project included the validation and development of assay platforms; workflows for data processing, management, exploration and visualization; and the establishment of protocols, quality control standards and standard operating procedures. Extensive infrastructure was established through a coordinated effort among the various HuB-MAP integration, visualization and engagement teams, tissue-mapping centres, technology and tools development and rapid technology implementation teams and working groups 1 . Single-cell maps, predominantly consisting of two-dimensional (2D) spatial data as well as data from dissociated cells, were generated for several organs. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) was established for open access to experimental tissue data and reference atlas data.The infrastructure was augmented with software tools for tissue data registration, processing, annotation, visualization, cell segmentation and automated annotation of cell types and cellular neighbourhoods from spatial data. Computational methods were developed for integrating multiple data types across scales and interpretation 2 . Standard reference terminology and a common coordinate framework spanning anatomical to biomolecular scales were established to ensure interoperability across organs, research groups and consortia 3 . Guidelines to capture high-quality multiplexed spatial data 4 were established including validated panels of cell-and structure-specific antibodies 5 . The first phase produced a large number of manuscripts (https://commonfund.nih.gov/ publications?pid=43) including spatially resolved single-cell maps [6][7][8][9][10][11] .The production phase of HuBMAP was launched in the autumn of 2022. The focus is on scaling data production spanning diverse biological variables (for example, age and ethnicity) and deployment and enhancement of analytical, visualization and navigational tools to generate high-resolution 3D accessible maps of major functional tissue units from more than 20 organs. This phase involves over 60 institutions and 400 researchers with opportunities for active intra-and inter-consortia collaborations and building a foundational resource for new biological insights and precision medicine. Below, ...

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Section: Perspectivementioning

confidence: 99%

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

et al. 2023

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“…Organ Mapping Antibody Panels (OMAPs, https://humanatlas.io/omap) are collections of antibodies designed for a particular sample preservation method and multiplexed imaging technology to allow spatial mapping of the anatomical structures and cell types present in the tissues for which they were validated 15,101 (see Fig. 1.…”

Section: Omaps and Avrsmentioning

confidence: 99%

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage

Börner,

Blood,

Silverstein

et al. 2024

Preprint

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The Human BioMolecular Atlas Program (HuBMAP) aims to construct a reference 3D structural, cellular, and molecular atlas of the healthy adult human body. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) serves experimental datasets and supports data processing, search, filtering, and visualization. The Human Reference Atlas (HRA) Portal (https://humanatlas.io) provides open access to atlas data, code, procedures, and instructional materials. Experts from more than 20 consortia are collaborating to construct the HRA's Common Coordinate Framework (CCF), knowledge graphs, and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes, and biomarkers) and to use the HRA to understand changes that occur at each of these levels with aging, disease, and other perturbations. The 6th release of the HRA v2.0 covers 36 organs with 4,499 unique anatomical structures, 1,195 cell types, and 2,089 biomarkers (e.g., genes, proteins, lipids) linked to ontologies. In addition, three workflows were developed to map new experimental data into the HRA's CCF. This paper describes the HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interface (APIs), flexible hybrid cloud infrastructure, and demonstrates first atlas usage applications and previews.

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“…Multiplexed imaging allows simultaneous measurement of dozens to thousands of molecular markers (RNA, protein, or metabolome) within single cells with high resolution spatial positioning (1–4). Technologies such as co-detection by indexing (CODEX), multiplexed ion beam imaging (MIBI), and others that employ multiplexed antibody detection (5–11) provide incredibly detailed spatial data due to standardization of reagents and procedures (12–15). Standardization of techniques and methods has enabled the collection of amply detailed spatial data (16–21) that have revealed spatial relationships between cells, with appropriate analysis regimens, furthered our understanding of disease states (22, 23), tissue organization (15), and progression of cancer (24, 25).…”

Section: Mainmentioning

confidence: 99%

SPACEc: A Streamlined, Interactive Python Workflow for Multiplexed Image Processing and Analysis

Tan,

Kempchen,

Becker

et al. 2024

Preprint

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Multiplexed imaging technologies provide insights into complex tissue architectures. However, challenges arise due to software fragmentation with cumbersome data handoffs, inefficiencies in processing large images (8 to 40 gigabytes per image), and limited spatial analysis capabilities. To efficiently analyze multiplexed imaging data, we developed SPACEc, a scalable end-to-end Python solution, that handles image extraction, cell segmentation, and data preprocessing and incorporates machine-learning-enabled, multi-scaled, spatial analysis, operated through a user-friendly and interactive interface.

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Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging

Cited by 17 publications

References 25 publications

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage

SPACEc: A Streamlined, Interactive Python Workflow for Multiplexed Image Processing and Analysis

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