Citation information

Citing MetaHQ

The preprint for MetaHQ can be found at https://arxiv.org/abs/2602.07805. To cite MetaHQ please use the following reference:

@misc{hicks2026metahqharmonizedhighqualitymetadata,
      title={MetaHQ: Harmonized, high-quality metadata annotations of public omics samples and studies},
      author={Parker Hicks and Lydia E Valtadoros and Christopher A Mancuso and Faisal Alquadoomi and Kayla A Johnson and Sneha Sundar and Arjun Krishnan},
      year={2026},
      eprint={2602.07805},
      archivePrefix={arXiv},
      primaryClass={q-bio.GN},
      url={https://arxiv.org/abs/2602.07805},
}

Citing individual annotation sets

Many annotations in the MetaHQ database are derived from external curation efforts. We require that users cite any sources that contributed to your retrieved annotation set.

  • Note: Sample and series annotation counts indicate how many individual sample- or series-level annotations a single source provides, not the number of samples or series. For example, Johnson_2023 may annotate tissue, disease, sex, and age for a single sample. This counts as four sample-level annotations.

1. ALE

2. Bgee

  • Source: Bgee: Gene Expression Data in Animals
  • License: CC0 1.0
  • Citation: Bastian FB, et al. (2021) The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals. Nucleic Acids Research 49(D1): D831–D847. https://doi.org/10.1093/nar/gkaa793
  • DOI: 10.1093/nar/gkaa793
  • Rights Statement: From web server
  • Access: https://www.bgee.org
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ

3. CellO

  • Source: CellO Cell Type Classification
  • License: CC BY 4.0
  • Citation: Bernstein, M. N., Ma, Z., Gleicher, M. & Dewey, C. N. CellO: Comprehensive and hierarchical cell type classification of human cells with the Cell Ontology. Iscience 24 (2021).
  • DOI: 10.1016/j.isci.2020.101913
  • Rights Statement: From Zenodo
  • Access: https://zenodo.org/records/4609473
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ

4. CREEDS

  • Source: CREEDS: CRowd Extracted Expression of Differential Signatures
  • License: CC BY 4.0
  • Citation: Wang, Z. et al. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd. Nature communications 7, 12846 (2016).
  • DOI: 10.1038/ncomms12846
  • Rights Statement: From web server
  • Access: https://maayanlab.cloud/CREEDS/
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ

5. DiSignAtlas

  • Source: DiSignAtlas
  • License: Free for academic usage only (NonCommercial)
  • Citation: Zhai, Z. et al. DiSignAtlas: an atlas of human and mouse disease signatures based on bulk and single-cell transcriptomics. Nucleic acids research 52, D1236–D1245 (2024).
  • DOI: 10.1093/nar/gkad961
  • Rights Statement: From web server
  • Access: http://www.inbirg.com/disignatlas/
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ
  • Commercial Use: For commercial usage, contact Prof. Jianbo Pan.
  • ⚠️ NonCommercial Restriction

6. Gemma

7. Golightly_2018

  • Source: Golightly, et al. (2018) Scientific Data
  • License: CC0 1.0
  • Citation: Golightly NP, et al. (2018) Curated compendium of human transcriptional biomarker data. Scientific Data 5: 180066. https://doi.org/10.1038/sdata.2018.66
  • DOI: 10.1038/sdata.2018.66
  • Rights Statement: From Rights and Permissions in paper
  • Access: https://osf.io/ssk3t/overview
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ

8. Gu_2023

  • Source: Gu, et al. (2023) Genomics, Proteomics & Bioinformatics
  • License: CC0 1.0
  • Citation: Gu, J., Dai, J., Lu, H. & Zhao, H. Comprehensive analysis of ubiquitously expressed genes in humans from a data-driven perspective. Genomics, Proteomics & Bioinformatics 21, 164–176 (2023).
  • DOI: 10.1016/j.gpb.2021.08.017
  • Rights Statement: From Rights and Permissions in paper
  • Access: Table S3 in https://academic.oup.com/gpb/article/21/1/164/7274179
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ

9. Johnson_2023

10. KrishnanLab

11. Sirota_2011

  • Source: Sirota, et al. (2011) Science translational medicine
  • License: CC BY-NC 3.0
  • Citation: Sirota, M. et al. Discovery and preclinical validation of drug indications using compendia of public gene expression data. Science translational medicine 3, 96ra77–96ra77 (2011).
  • DOI: 10.1126/scitranslmed.3001318
  • Access: Table S1 in https://www.science.org/doi/10.1126/scitranslmed.3001318
  • Note: No explicit license declaration was found. However, this source is published under the Science Translational Medicine AAAS Open Access program that allows for CC BY and CC BY-NC licenses. We assume the strictest.
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ
  • ⚠️ NonCommercial Restriction

12. URSA

  • Source: URSA (Unveiling RNA Sample Annotation)
  • License: CC BY-NC 3.0
  • Citation: Lee, Y., Krishnan, A., Zhu, Q. & Troyanskaya, O. G. Ontology-aware classification of tissue and cell-type signals in gene expression profiles across platforms and technologies. Bioinformatics 29, 3036–3044 (2013).: 152-162.e6. https://doi.org/10.1016/j.cels.2018.12.010
  • DOI: 10.1093/bioinformatics/btt529
  • Rights Statement From Permissions in paper
  • Access: Access through the MetaHQ database at https://doi.org/10.5281/zenodo.17663086.
  • Notes: The original web server that housed these annotations (ursa.princeton.edu) is no longer active.
  • Sample annotations in MetaHQ
  • Series annotations in MetaHQ
  • ⚠️ NonCommercial Restriction

13. URSA_HD