Batch correction and harmonization of –Omics datasets with a tunable median polish of ratio
Open accessAbstract
Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in -omics data. We also show how TAMPOR can be used to harmonize -omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of -omics data prior to downstream systems biology analysis.
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TAMPOR removes intra-batch and inter-batch variance while preserving meaningful biological variance.
“TAMPOR is utilized to remove intra-batch and inter-batch variance while preserving meaningful biological variance in protein abundance values, normalizing to the median of selected samples within batch.”
From APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology (2025) · cites this paper as [37]
The Discussion says TAMPOR minimizes variance across batches while maintaining biological variance and differences between samples within a batch. The Results also describe correcting unequal sample loading, but the source does not support removing intra-batch variance generally; that wording overlooks the within-batch variance TAMPOR is designed to preserve. The Discussion supports the use of the median of selected or all samples for normalization. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFewer than one-third of published multi-omics AD studies release full code and preprocessing parameters, limiting independent validation.
“However, fewer than one-third of published multi-omics AD studies release full code and preprocessing parameters, limiting independent validation254.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [254]
The Introduction discusses batch artifacts and challenges in harmonizing AD omics datasets, while the Discussion addresses the potential benefits of harmonization; neither reports a survey of published studies. Searches for code availability, preprocessing parameters, and independent validation found no passage supporting the fewer-than-one-third figure. (LLM, conf=0.74)
Experimental — accuracy not yet measured
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Cites
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Ren, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
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Self-citation
- Authors
- Dammer, E. B., Seyfried, N. T., & Johnson, E. C. B.
- Affiliations
- Emory University (US)
- Corresponding author
- Dammer, Eric B.
- Venue
- Frontiers in Systems Biology
- Publisher
- Frontiers Media SA
- Published
- 2023-04-12
- Volume
- 3
- ISSN
- 2674-0702 (ISSN-L)
- PMC
- PMC10137904
- OpenAlex
- W4364360591
- Cited by
- 53
- References
- 3
- Citations by year
- 2026: 16 · 2025: 19 · 2024: 13 · 2023: 5
- FWCI
- 4.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Systems Biology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (K08AG068604 U01AG061357)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- 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
- Keywords
- batch effect correction, technical artifacts, proteomics, quality control metrics
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