Guidelines for the design, analysis and interpretation of ‘omics’ data: focus on human endometrium
Open accessAbstract
BACKGROUND: 'Omics' high-throughput analyses, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, are widely applied in human endometrial studies. Analysis of endometrial transcriptome patterns in physiological and pathophysiological conditions has been to date the most commonly applied 'omics' technique in human endometrium. As the technologies improve, proteomics holds the next big promise for this field. The 'omics' technologies have undoubtedly advanced our knowledge of human endometrium in relation to fertility and different diseases. Nevertheless, the challenges arising from the vast amount of data generated and the broad variation of 'omics' profiling according to different environments and stimuli make it difficult to assess the validity, reproducibility and interpretation of such 'omics' data. With the expansion of 'omics' analyses in the study of the endometrium, there is a growing need to develop guidelines for the design of studies, and the analysis and interpretation of 'omics' data. METHODS: Systematic review of the literature in PubMed, and references from relevant articles were investigated up to March 2013. RESULTS: The current review aims to provide guidelines for future 'omics' studies on human endometrium, together with a summary of the status and trends, promise and shortcomings in the high-throughput technologies. In addition, the approaches presented here can be adapted to other areas of high-throughput 'omics' studies. CONCLUSION: A highly rigorous approach to future studies, based on the guidelines provided here, is a prerequisite for obtaining data on biological systems which can be shared among researchers worldwide and will ultimately be of clinical benefit.
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Many centres worldwide have been collecting blood or other body fluids such as peritoneal fluid, endometrial fluid, and menstrual fluid, as well as tissue samples-in particular ectopic and eutopic endometrium-from women with and without endometriosis, for a variety of research purposes.
“Many centres worldwide have been collecting blood or other body fluids such as peritoneal fluid, endometrial fluid, and menstrual fluid, as well as tissue samples—in particular ectopic and eutopic endometrium—from women with and without endometriosis, for a variety of research purposes [145–147].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [145]
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Self-citationAssessing sirtuin expression in endometrial carcinoma and non-neoplastic endometrium
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Self-citationEndometrial receptivity and pregnancy outcome
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Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer
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Self-citationHuman S100A10 plays a crucial role in the acquisition of the endometrial receptivity phenotype
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Activated Platelets Induce Estrogen Receptor β Expression in Endometriotic Stromal Cells
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Metabolomics for improving pregnancy outcomes in women undergoing assisted reproductive technologies
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An update on the progress of transcriptomic profiles of human endometrial receptivity†
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Morphomics: An integral part of systems biology of the human placenta
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Essential Role of CRIM1 on Endometrial Receptivity in Goat
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Self-citationMicroRNAs, small regulatory elements with significant effects on human implantation: a review
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Reproductive Endocrinology in Recurrent Pregnancy Loss
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Sensomics - basic principles and practice
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Guan, H., Zhao, S., Li, J., Wang, Y., Niu, P., Zhang, Y., Zhang, Y., Fang, X., Miao, R., & Tian, J. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1363877 · Cited by 17 · see citing works
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Plaza‐Florido, A., Pérez‐Prieto, I., Molina‐García, P., Radom‐Aizik, S., Ortega, F. B., & Altmäe, S. (2022) · Frontiers in Pediatrics · doi:10.3389/fped.2022.917152 · Cited by 16 · see citing works
Self-citationMapping Human Uterine Disorders Through Single-Cell Transcriptomics
Boldu-Fernández, S., Lliberos, C., Simón, C., & Mas, A. (2025) · Cells · doi:10.3390/cells14030156 · Cited by 17 · see citing works
Self-citationRicard‐Blum, S., & Miele, A. E. (2019) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2019.12.009 · Cited by 15 · see citing works
Embryo secretome in predicting embryo quality and IVF treatment outcome
Toporcerová, S., Badovská, Z., Kriváková, E., Mikulová, V., Mareková, M., Altmäe, S., & Rabajdová, M. (2025) · Reproductive BioMedicine Online · doi:10.1016/j.rbmo.2025.104825 · Cited by 14 · see citing works
Self-citationVargas, E., Aghajanova, L., Gemzell‐Danielsson, K., Altmäe, S., & Esteban, F. J. (2019) · Reproductive BioMedicine Online · doi:10.1016/j.rbmo.2019.11.003 · Cited by 13 · see citing works
Self-citationSilveira, C. O., Rezende, C. P., Ferreira, M. C. F., Puerto, H. L. D., & dos Reis, F. M. (2016) · Reproductive Sciences · doi:10.1177/1933719116667490 · Cited by 14 · see citing works
Liang, X., He, J., He, L., Lin, Y., Li, Y., Cai, K., Wei, J. J., Lu, Y., & Chen, Z. (2023) · Reproductive BioMedicine Online · doi:10.1016/j.rbmo.2023.03.015 · Cited by 13 · see citing works
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Gatius, S., Jové, M., Megino‐Luque, C., Albertí‐Valls, M., Yeramian, A., Bonifaci, N., Piñol, M., Santacana, M., Pradas, I., Llobet‐Navàs, D., et al. (2022) · Cancers · doi:10.3390/cancers14122842 · Cited by 11 · see citing works
Reproductomics: Exploring the Applications and Advancements of Computational Tools
Sengupta, P., Dutta, S., Liew, F. F., Samrot, A. V., Dasgupta, S., Rajput, M., Sláma, P., Kolesárová, A., & Roychoudhury, S. (2024) · Physiological Research · doi:10.33549/physiolres.935389 · Cited by 10 · see citing works
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The endometrial transcriptome of infertile women with and without implantation failure
Bui, B. N., Kukushkina, V., Meltsov, A., Olsen, C., van Hoogenhuijze, N. E., Altmäe, S., Mol, F., Teklenburg, G., de Bruin, J. P., Besselink, D. E., et al. (2024) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.14822 · Cited by 9 · see citing works
Self-citationModern approaches to endometrial receptivity assessment (a review)
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Hu, S., Sun, Z., Li, B., Zhao, H., Wang, Y., Yao, G., Li, X., Bian, X., Li, T. C., Vankelecom, H. E. J., et al. (2023) · Endocrinology · doi:10.1210/endocr/bqad012 · Cited by 9 · see citing works
The endometrial proteomic profile around the time of embryo implantation†
Guo, X. W., Li, T. C., & Chen, X. (2020) · Biology of Reproduction · doi:10.1093/biolre/ioaa150 · Cited by 9 · see citing works
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OMICs Studies and Endometriosis Biomarker Identification
Saare, M., Peters, M., Aints, A., Laisk, T., Salumets, A., & Altmäe, S. (2017) · Springer eBooks · doi:10.1007/978-3-319-59856-7_12 · Cited by 8 · see citing works
Self-citationHuang, X. H., Xiao, L. Y., Long, Y., Pei, T., Luo, B., Liao, T., Li, Y., Zhu, H., Ouyang, Y., & Huang, W. (2022) · Reproductive Sciences · doi:10.1007/s43032-022-00869-3 · Cited by 9 · see citing works
DNA Repair Gene XRCC1 and XRCC4 Variations and Risk of Endometriosis: An Association Study
Saliminejad, K., Saket, M., Kamali, K., Memariani, T., & Khorshid, H. R. K. (2015) · Gynecologic and Obstetric Investigation · doi:10.1159/000366444 · Cited by 7 · see citing works
Uterine Transcriptome: Understanding Physiology and Disease Processes
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- Authors
- Altmäe, S., Esteban, F. J., Stavreus-Evers, A., Simón, C., Giudice, L., Lessey, B. A., Horcajadas, J. A., Macklon, N. S., D'Hooghe, T., Campoy, C., Fauser, B. C., Salamonsen, L. A., & Salumets, A.
- Affiliations
- Universidad de Granada (ES)
- Universidad de Jaén (ES)
- Uppsala University (SE)
- Valencian Infertility Institute (ES)
- University of California, San Francisco (US)
- Prisma Health (US)
- Fundacion Agencia Aragonesa para la Investigacion y el Desarrollo (ES)
- Princess Anne Hospital (GB)
- University Medical Center Utrecht (NL)
- Competence Centre on Health Technologies (Estonia) (EE)
- ORCID
- Venue
- Human Reproduction Update
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-09-29
- Volume
- 20
- Issue
- 1
- Pages
- 12-28
- ISSN
- 1355-4786 (ISSN-L)
- 1460-2369
- PMC
- PMC3845681
- OpenAlex
- W2143750395
- Cited by
- 151
- References
- 201
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 15 · 2023: 12 · 2022: 10 · 2021: 9 · 2020: 14 · 2019: 16 · 2018: 14 · 2017: 16 · 2016: 12 · 2015: 16 · 2014: 6
- FWCI
- 1.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- Human Reproduction Update (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Institutional Repository of the University of Granada (University of Granada) (submittedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- European Commission (329812)
- State Government of Victoria
- Ettevõtluse Arendamise Sihtasutus (EU324509, EU30020)
- National Institutes of Health
- National Health and Medical Research Council (494802, 1002028)
- National Institute of Child Health and Human Development
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD067721)
- Eurostars
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- human endometrium, omics data, data analysis and interpretation, transcriptomics, proteomics, metabolomics, epigenomics, high-throughput technologies, reproducibility, endometrial disease
- MeSH terms
- Endometrium, Female, Humans, Embryo Implantation, Guidelines as Topic, Genomics, Systems Biology, Metabolomics, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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