Order Matters: Ambient RNA correction confounds doublet detection in single-cell RNA sequencing
Open accessAbstract
A common technical artifact in droplet-based single-cell RNA sequencing (scRNA-seq) is the capture of two cells in the same droplet, termed doublets. Doublets may present as hybrid cell types, and their removal is a critical step during quality control. Another form of contamination is ambient RNA, which originates from free floating RNA released from other cells in suspension, likely during cell death. As with doublets, ambient RNA results in unexpected gene expression patterns. Most suggested analysis pipelines include ambient RNA correction before doublet detection however no formal investigation into how doublet detection is affected by ambient RNA correction has been conducted. Here, we evaluate the impact of ambient RNA correction on the performance of doublet detection using novel engineered and multiplexed datasets. We apply three of the most widely-used methods for removing ambient RNA (decontX, soupX, CellBender), in conjunction with up to six doublet detection methods (scDblFinder, scds, bcds, cxds, scrublet, DoubletDetection). We find that doublet detection tools perform best when done prior to ambient RNA correction, with the exception of CellBender. Performing ambient RNA correction first, particularly for decontX, leads to an increased proportion of doublet droplets retained in the dataset compared with calling doublets on uncorrected data. We show that both decontX and soupX partially mask doublet signal by removing proportionally more ambient RNA from doublets that remain undetected after ambient RNA correction. Our results show that the performance of doublet detection is significantly impacted by the use of ambient RNA correction tools. We suggest a new workflow that implements doublet detection prior to ambient RNA correction unless using CellBender.
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Research works printed but not linked: 1
- 10.1101/2025.06.09.658708 · DOI
- Authors
- Meier, M., Howitt, G., Grima, C. V., Dixit, G., King, H., Gubbels, L., Levi, E., Davies, K., Shanthikumar, S., Neeland, M. R., Maksimovic, J., & Oshlack, A.
- Affiliations
- The University of Melbourne (AU)
- Walter and Eliza Hall Institute of Medical Research (AU)
- Murdoch Children's Research Institute (AU)
- Royal Children's Hospital (AU)
- Corresponding author
- Oshlack, Alicia
- ORCID
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2026-10-17
- OpenAlex
- W7222864701
- Semantic Scholar
- e3136de797027ec4cb3e165aad04fb2761ca3471
- Cited by
- 0
- References
- 55
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Funders
- Australian Government Research Training Program Scholarship (DOI: https://doi.org/10.82133/C42F-K220)
- National Health and Medical Research Council (1196256, 2026098, 2019360)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- doublet detection, single-cell RNA sequencing, data processing workflow, technical artifacts
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