Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
Thanks to a stringent selection of well-designed datasets, we demonstrate that quality imbalance between groups of samples can significantly reduce the relevance of differential genes, consequently reducing reproducibility between studies. Appropriate experimental design and analysis methods can substantially reduce the problem.
Authors
- Miguel A. Andrade‐Navarro (ORCID: https://orcid.org/0000-0001-6650-1711)
- Maximilian Sprang (ORCID: https://orcid.org/0000-0002-8438-4747)
- Jean−Fred Fontaine
- Jannik S. Möllmann (ORCID: https://orcid.org/0000-0002-4850-9418)
Institutions
- Johannes Gutenberg University Mainz (DE)
- Krankenhaus vom Roten Kreuz (DE)
Publication Details
- Journal
- Genome biology
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1186/s13059-024-03331-6
- Citations
- 4
- Primary Topic
- Molecular Biology Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.94