DICOM converted whole slide hematoxylin and eosin stained images from the Genotype-Tissue Expression (GTEx) Project

This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute Imaging Data Commons (IDC) [1]. This dataset was converted into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using IDC Portal here: GTEx. You can use the manifests included in this Zenodo record to download the content of the collection following the Download instructions below.

Collection description

The Genotype-Tissue Expression (GTEx) Project established a data resource and tissue bank to study the relationship between genetic variants and gene expression in multiple human tissues and across individuals. The project included contributions from numerous groups with diverse expertise in biospecimen collection and processing, pathology review, molecular analysis, and data management. The contributors are collectively called the GTEx Consortium.

GTEx collected a total of 26,468 unique tissue samples from 50+ different tissue types, from 956 healthy postmortem donors. The standardized biospecimen collection and analysis practices applied during the study served to minimize preanalytical variability associated with specimen-related factors and their potential impact on analytic endpoints. Each GTEx tissue was divided into two tissue blocks, one for histology and one for molecular analysis; both tissue blocks were preserved in PAXgene Tissue Fixative (Qiagen) solution for 6 to 24 hours, followed by PAXgene Tissue Stabilizer (Qiagen) as specified in the project-specific standard operating procedures. Tissue blocks were processed and embedded in paraffin at the GTEx central repository at the Van Andel Institute (MI) and hematoxylin and eosin–stained slides were generated from all GTEx donors. Digitally scanned whole slide images of PAXgene-fixed/stabilized, paraffin-embedded tissue sections were created using Aperio Scanscope software (Leica Biosystems). The digital images were then reviewed and annotated by one of four board-certified pathologists assigned to the GTEx study. There are a total of 25,503 digital histology images in the GTEx collection.

GTEx was supported by the NIH Common Fund (2010 – 2019).  Additional resources include the GTEx Biobank, the GTEx Portal, and the full dataset at dbGaP (accession number phs000424).

Please refer to the listed GTEx publications below for more details [2-7]. 

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced. For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the collection_id collection introduced in IDC data release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of the corresponding collection was introduced.

1. gtex-idc_v19-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets
2. gtex-idc_v19-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets
3. gtex-idc_v19-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)

Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.

Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:

1. install idc-index package: pip install --upgrade idc-index
2. download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd

To download the files using .dcf manifest, see manifest header.

Acknowledgments

The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (commonfund.nih.gov/GTEx). Additional funds were provided by the NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Donors were enrolled at Biospecimen Source Sites funded by NCI/Leidos Biomedical Research, Inc. subcontracts to the National Disease Research Interchange (10XS170), Roswell Park Cancer Institute (10XS171), and Science Care, Inc. (X10S172). The Laboratory, Data Analysis, and Coordinating Center (LDACC) was funded through a contract (HHSN268201000029C) to the Broad Institute of MIT and Harvard. Biorepository operations were funded through a Leidos Biomedical Research, Inc. subcontract to Van Andel Research Institute (10ST1035). Additional data repository and project management were provided by Leidos Biomedical Research, Inc. (HHSN261200800001E). The Brain Bank was supported with supplements to University of Miami grant DA006227. Statistical Methods development grants were made to the University of Geneva (MH090941& MH101814), the University of Chicago (MH090951, MH090937, MH101825, & MH101820), the University of North Carolina - Chapel Hill (MH090936), North Carolina State University (MH101819), Harvard University (MH090948), Stanford University (MH101782), Washington University (MH101810), and to the University of Pennsylvania (MH101822).

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.

References

[1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W. L., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. National cancer institute imaging data commons: Toward transparency, reproducibility, and scalability in imaging artificial intelligence. Radiographics 43, (2023).

[2] Sobin, L., Barcus, M., Branton, P. A., Engel, K. B., Keen, J., Tabor, D., Ardlie, K. G., Greytak, S. R., Roche, N., Luke, B., Vaught, J., Guan, P. & Moore, H. M. Histologic and quality assessment of genotype-Tissue Expression (GTEx) research samples: A large postmortem tissue collection. Arch. Pathol. Lab. Med. (2024). doi:10.5858/arpa.2023-0467-OA

[3] GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).

[4] GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

[5] GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).

[6] Carithers, L. J., Ardlie, K., Barcus, M., Branton, P. A., Britton, A., Buia, S. A., Compton, C. C., DeLuca, D. S., Peter-Demchok, J., Gelfand, E. T., Guan, P., Korzeniewski, G. E., Lockhart, N. C., Rabiner, C. A., Rao, A. K., Robinson, K. L., Roche, N. V., Sawyer, S. J., Segrè, A. V., Shive, C. E., Smith, A. M., Sobin, L. H., Undale, A. H., Valentino, K. M., Vaught, J., Young, T. R., Moore, H. M. & GTEx Consortium. A novel approach to high-quality postmortem tissue procurement: The GTEx project. Biopreserv. Biobank. 13, 311–319 (2015).

[7] Branton, P. A., Sobin, L., Barcus, M., Engel, K. B., Greytak, S. R., Guan, P., Vaught, J. & Moore, H. M. Notable histologic findings in a ‘normal’ cohort: The National Institutes of Health Genotype-Tissue Expression (GTEx) project. Arch. Pathol. Lab. Med. (2024). doi:10.5858/arpa.2023-0468-OA