Metadata Reporting Standards

Sample Suspension

Suspension is a sample preparation format in which cells, organelles, or other biological particles are dispersed as individual units within a liquid medium. Suspension-based assays are commonly used in flow cytometry, single-cell sequencing, and multiplexed molecular screening where dissociation of tissue into single-cell suspensions is required prior to analysis. This format enables high-throughput, per-cell measurements but does not preserve the spatial context of the original tissue.

DOI: https://doi.org/10.35079/HBM437.GKTS.458

Published: September 16, 2026

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MD5 hash: 73ab7ff0559410c7a51db7611c2d6b58

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Schema

Legend: Text field Allowable value Radio Numeric

* Required

Attribute Type Description Allowable Values
Source ID * The unique identifier from HuBMAP or SenNet for the source (parent data) from which the sample was derived. Example: HBM122.EFGH.789  
Sample ID * The unique HuBMAP or SenNet identifier assigned to the sample by the ingest portal. Example: HBM743.CKJW.876  
Lab ID A locally assigned identifier provided by the data provider for the dataset. It is used to reference an external metadata record that may be maintained independently, enabling traceability and supporting provenance tracking. Example: Visium_9OLC_A4_S1  
Preparation protocol DOI * The DOI for the protocols.io page that details the assay or the procedures used for sample procurement and preparation. For example, in the case of an imaging assay, the protocol may start with tissue section staining and end with the generation of an OME-TIFF file. The documented protocol should also include any image processing steps involved in producing the final OME-TIFF. Example: https://dx.doi.org/10.17504/protocols.io.eq2lyno9qvx9/v1  
Source storage duration value * The length of time the sample was stored prior to processing it. For assays performed on tissue sections, this refers to how long the tissue section (e.g., slide) was stored before the assay began (e.g., imaging). For assays performed on suspensions, such as sequencing, it refers to how long the suspension was stored before library construction started. Example: 12  
Source storage duration unit * The unit of measurement used to specify the source storage duration value. Example: hour hour month year day minute
Tissue weight value The weight of a tissue block or the piece of tissue used in a suspension. This information is crucial for calculating the percentage of the parent block that was utilized in the suspension preparation. If the weight is not applicable or unknown, this field may be left blank. Example: 100  
Tissue weight unit The unit of measurement for the tissue weight value. If no tissue weight is specified, this field may be left blank. Example: g ug g mg kg
Preparation medium * The medium used during the sample preparation process. If no specific medium was utilized, enter “None”. If medium was not recorded, enter “Unknown”. Example: Fresh frozen CMC HTK Solution NBF (Neutral Buffered Formalin) Allprotect tissue reagent (ALL) CLARITY hydrogel Trumps fixative 1X fixation & permeabilization buffer Inflated (OCT) DMEM Perfadex Plus PFA (Paraformaldehyde) Fixed frozen OCT (Formalin, sucrose protected) Unknown Fresh frozen OCT Alpha-MEM 2% PFA/2.5% Glutaraldehyde Bouin's Methanol PAXgene tissue kit (PXT) PBS Ethanol Modified Davidson's Fixative HPMC-PVP Inflated (Agarose) PLP (Periodate-Lysine-Paraformaldehyde) UW Solution MACS tissue storage solution Fresh frozen CMC Fresh frozen gelatin Growth media RNAlater Biops buffer Fixed frozen OCT (Cytofix/Cytoperm) None Fixed frozen OCT (PFA, sucrose protected) Lysis buffer
Preparation condition * The condition under which the sample preparation took place, such as whether the sample was placed on dry ice during the process. If preparation condition was not recorded, enter “Unknown”. Example: Frozen on dry ice Frozen in liquid nitrogen vapor Stored in ambient temperature Frozen on ice Frozen in liquid nitrogen Unknown Incubated at 37 degrees celsius Frozen at -20 degrees celsius Frozen on dry ice Stored in refrigerator Stored on wet ice
Processing time value The duration for which the tissue was handled prior to its initial preservation. Example: 120  
Processing time unit The unit of measurement for the processing time value. If processing time is not specified, this field may be left blank. Example: minute hour day minute
Storage medium * The medium used to preserve the sample. If no specific medium was utilized, enter “None”. If medium was not recorded, enter “Unknown”. Example: FFPE (Paraffin embedded) Water OCT NBF (Neutral Buffered Formalin) Allprotect tissue reagent (ALL) DMSO (no serum) PFA (Paraformaldehyde) Unknown Gelatin DMSO (serum) CMC Nuclease-free water 2% PFA/2.5% Glutaraldehyde Methanol PAXgene tissue kit (PXT) PBS 1X quench buffer Ethanol Formic acid in water HPMC-PVP MACS tissue storage solution Tris-EDTA Concentrated quench buffer Cryo-EM RNAlater FFPE (Paraffin embedded) None
Storage method * The method used to store the sample after preparation and prior to performing the assay. If no specific storage method was utilized, enter “None”. If storage method was not recorded, enter “Unknown”. Example: Frozen in dry ice Frozen in liquid nitrogen vapor Stored in ambient temperature Frozen on ice Frozen in liquid nitrogen Unknown Stored in desiccator Incubated at 37 degrees celsius Frozen at -80 degrees celsius Frozen at -20 degrees celsius Frozen on dry ice Stored in refrigerator None
Quality criteria The quality criteria used to assess the sample, which may include metrics such as RIN (e.g., RIN: 8.7) or visual inspection parameters for suspensions prior to cell lysis. These criteria can be captured at a high level with general terms like “OK” or “not OK” or with more specific descriptors such as “debris” “clump” or “low clump”. Example: RIN: 8.7, low clump, no visible debris  
Suspension entity type * The type of single-cell entity that is derived from the isolation protocol. Example: Nucleus + cell Nucleus + cell Nucleus cDNA Cell
Suspension entity count * The total number of cells or nuclei obtained following the processes of dissociation and enrichment. Example: 300000  
Is suspension enriched? * Indicates whether the cell or nuclei population was enriched prior to analysis. Example: Yes Yes No
Suspension enriched target The target of enrichment if the suspension was enriched. Example: CD8+ T cells  
Notes Miscellaneous details about the sample that are not captured in the existing metadata fields. Example: Sample was stored at 4°C for 48 hours prior to processing due to equipment maintenance delay  
Metadata schema ID * The unique string identifier for the metadata specification version, which is easily interpretable by computers for purposes of data validation and processing. Example: 22bc762a-5020-419d-b170-24253ed9e8d9  
CEDAR OpenView Documentation CEDAR Validator

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Citation

Fisher SA, Hardi J, Morgan R, Nordgren E, Kant PM, Honick B, Rosario J, O'Connor MJ, Turner ML, DCWG Members, Gehlenborg N, Blood PD, Silverstein JC, Musen MA. 2026. The HuBMAP Framework for Advancing Data FAIRness. submitted. https://doi.org/10.64898/2026.06.01.728946


Reuse

This standard may be reused, expanded, or referenced by external repositories. It represents version 2.1 of the metadata schema. If you are uploading data, the latest version is available at the "Latest Version" link below. If you are querying or using HuBMAP or SenNet metadata, a harmonized view of the metadata specification is available at the "Harmonized Version" link below.


Latest Version    Harmonized Version

Contributors

Below is the information for the individuals who contributed to the HuBMAP and SenNet metadata reporting standards.

For questions about this standard, email HuBMAP Helpdesk. You can alternatively reach out to the individuals listed below, either via the email address listed in the table or via contact information provided on their ORCID profile page.

Name Affiliation Contact ORCID
Stephen A Fisher University of Pennsylvania, Philadelphia PA, USA safisher@upenn.edu 0000-0001-8034-7685
Josef Hardi Stanford University, Stanford, CA, USA johardi@stanford.edu 0000-0002-2533-6681
Richard Morgan University of Pittsburgh, Pittsburgh, PA, USA rsm66@pitt.edu 0009-0003-1800-8545
Mark A Musen Stanford University, Stanford, CA, USA musen@stanford.edu 0000-0003-3325-793X
Jonathan C Silverstein University of Pittsburgh, Pittsburgh, PA, USA j.c.s@pitt.edu 0000-0002-9252-6039
Erik Nordgren University of Pennsylvania, Philadelphia PA, USA   0000-0002-5024-0278
Peter M Kant University of Pittsburgh, Pittsburgh, PA, USA; Currently - Otsuka Precision Health, Princeton, NJ, USA   0009-0002-6510-5041
Brendan John Honick Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA   0000-0001-6128-9854
Martin J O’Connor Stanford University, Stanford, CA, USA   0000-0002-2256-2421
Jean G Rosario University of Pennsylvania, Philadelphia PA, USA   0000-0002-6116-5058
Nils Gehlenborg Harvard Medical School, Boston, MA, USA   0000-0003-0327-8297
Philip D Blood Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA   0000-0002-9129-1223
Kyung Jin Ahn Children’s Hospital of Philadelphia, Philadelphia, PA, USA   0000-0002-4184-482X
Christopher R Anderton Pacific Northwest National Laboratory, Richland, WA, USA   0000-0002-6170-1033
Shovik Bandyopadhyay Children’s Hospital of Philadelphia, Philadelphia, PA, USA; Brigham and Women’s Hospital, Boston, MA, USA   0000-0003-3919-3914
Kenneth C Bedi University of Pennsylvania, Philadelphia PA, USA   0000-0003-3588-9324
Maigan Brusko University of Florida, Gainesville, FL, USA   0000-0002-4331-2202
Martha Campbell-Thompson University of Florida, Gainesville, FL, USA   0000-0001-6878-1235
James Carson The University of Texas at Austin, Austin, TX, USA   0000-0001-9009-5645
Chase M Carver Mayo Clinic, Rochester, MN, USA   0000-0003-4002-2418
Jing Chen University of Florida, Gainesville, FL, USA   0000-0001-8008-8062
Anthony M Corbett University of Rochester Medical Center, Rochester, NY, USA   0000-0001-9545-0853
Alexandra E Cuaycal University of Florida, Gainesville, FL, USA   0000-0002-9060-6326
Penny Cuda Carnegie Mellon University, Pittsburgh, PA, USA   0009-0002-6547-2650
Dinh Diep University of California, San Diego, CA, USA; Currently - Altos Labs, San Diego, CA, USA   0000-0001-6057-4119
Sergii Domanskyi The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA   0000-0002-6847-6019
Sean Donahue Carnegie Mellon University, Pittsburgh, PA, USA   0000-0002-4072-2046
Michael P Duffy University of Pennsylvania, Philadelphia PA, USA   0000-0001-5325-3683
Michael T Eadon Indiana University School of Medicine, Indianapolis, IN, USA   0000-0003-3066-2876
Jean Fan Johns Hopkins University, Baltimore, MD, USA   0000-0002-0212-5451
Melissa A Farrow Vanderbilt University, Nashville, TN, USA   0000-0002-1602-2082
Kathleen M Fisch University of California San Diego, La Jolla, CA, USA   0000-0002-0117-7444
William F Flynn The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA   0000-0001-6533-0340
James M Fulcher Pacific Northwest National Laboratory, Richland, WA, USA   0000-0001-9033-3623
Soumya Ghose GE HealthCare, Niskayuna, NY, USA   0000-0002-2730-1482
Fiona Ginty GE HealthCare, Niskayuna, NY, USA   0000-0001-6638-683X
Joana P Gonçalves Delft University of Technology, Delft, The Netherlands   0000-0001-6072-9627
Yongqun He University of Michigan, Ann Arbor, MI, USA   0000-0001-9189-9661
Po Hu Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA   0000-0003-2422-1652
Sanjay Jain Washington University School of Medicine, St. Louis, MO, USA   0000-0003-2804-127X
Thomas V Karathanos Stanford University, Stanford, CA, USA   0000-0003-1754-3872
Madhurima Kaushal Washington University School of Medicine   0000-0003-2760-0586
Angela RS Kruse Vanderbilt University, Nashville, TN, USA; Currently - The Ohio State University, Columbus, OH, USA   0000-0001-8776-2769
Yumi Kwon Pacific Northwest National Laboratory, Richland, WA, USA   0000-0003-0523-6197
Blue B Lake University of California San Diego, La Jolla, CA, USA; Currently - Altos Labs, San Diego, CA, USA   0000-0002-8637-9044
Roy Lardenoije Delft University of Technology, Delft, The Netherlands   0000-0002-9026-7870
Shin Lin Emory University, Atlanta, GA, USA   0000-0003-0118-0413
Yiing Lin Washington University, St. Louis, MO, USA   0000-0002-0317-7608
Scott A Lindsay University of California, San Diego, CA, USA   0000-0002-2929-7755
Peiran Lu Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA   0009-0001-5096-3046
Clayton Mathews University of Florida, Gainesville, FL, USA   0000-0002-8817-6355
Elizabeth McDonough GE HealthCare, Niskayuna, NY, USA   0000-0001-7524-8260
Ricardo Melo Ferreira Indiana University School of Medicine, Indianapolis, IN, USA   0000-0003-2063-9744
Emma M Monte Stanford University, Stanford, CA, USA   0000-0003-2566-1967
Kathleen O’Neill University of Pennsylvania, Philadelphia PA, USA   0000-0003-1980-6840
Minxing Pang University of Pennsylvania, Philadelphia PA, USA   0000-0001-5208-5972
Mana Parast University of California San Diego, La Jolla, CA, USA   0000-0001-5963-2246
Liming Pei Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA   0000-0002-1924-0333
Samuel Peters University of Minnesota, Minneapolis, MN, USA   0000-0003-1479-8087
Ajay Pillai National Institute of Health, Bethesda, MD, USA   0000-0002-9789-7189
Gloria Pryhuber University of Rochester Medical Center, Rochester, NY, USA   0000-0002-9185-3994
Ling Qin University of Pennsylvania, Philadelphia PA, USA   0000-0002-2582-0078
Presha Rajbhandari Columbia University, NYC, NY, USA   0000-0003-2184-7238
Matthew M Ruffalo Carnegie Mellon University, Pittsburgh, PA, USA   0000-0003-2222-6169
Pinaki Sarder University of Florida, Gainesville, FL, USA   0000-0003-2450-5233
Diane C Saunders Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA; Northwestern University, Chicago, IL, USA   0000-0002-8849-6746
Kevin Schneider Buck Institute, Novato, CA, USA   0009-0001-8046-0167
Lingyan Shi University of California San Diego, La Jolla, CA, USA   0000-0003-1373-3206
Santhosh Sivajothi The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA   0000-0002-8854-4517
David Smith Children’s Hospital of Philadelphia, Philadelphia, PA, USA   0000-0001-7858-3785
Jeff M Spraggins Vanderbilt University, Nashville, TN, USA   0000-0001-9198-5498
Valentina Stanley University of California, San Diego, CA, USA   0000-0002-2212-7796
Kai Tan Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA   0000-0002-9104-5567
Anusha Thadi Children’s Hospital of Philadelphia, Philadelphia, PA, USA   0000-0002-1271-0398
Hua Tian Columbia University Medical Center, NYC, NY, USA   0000-0002-3598-0219
Morgan L Turner Harvard Medical School, Boston, MA, USA   0000-0002-1512-9742
Ioannis S Vlachos Beth Israel Deaconess Medical Center, Boston, MA, USA; Harvard Cancer Center, Boston, MA, USA; Broad Institute of MIT and Harvard, Boston, MA, USA   0000-0002-8849-808X
Seth Winfree University of Nebraska Medical Center, Omaha, NE, USA; Currently - QCDx Inc, Farmington, CT, USA    
Pei-Hsun Wu Johns Hopkins University, Baltimore, MD, USA   0000-0002-7371-2960
Kevin J Zemaitis Pacific Northwest National Laboratory, Richland, WA, USA   0000-0002-3524-9776
Mowei Zhou Pacific Northwest National Laboratory, Richland, WA, USA; Currently - Zhejiang University, Hangzhou, Zhejiang 310058, China   0000-0003-3575-3224
Chenchen Zhu Department of Genetics, Stanford University, Stanford, CA, USA   0000-0003-2165-9456