SpotClean adjusts for spot swapping in spatial transcriptomics data

Zijian Ni, Aman Prasad, Shuyang Chen, Richard B. Halberg, Lisa M. Arkin, Beth A. Drolet, Michael A. Newton and Christina Kendziorski ()
Additional contact information
Zijian Ni: University of Wisconsin-Madison
Aman Prasad: University of Wisconsin-Madison
Shuyang Chen: University of Wisconsin-Madison
Richard B. Halberg: University of Wisconsin-Madison
Lisa M. Arkin: University of Wisconsin-Madison
Beth A. Drolet: University of Wisconsin-Madison
Michael A. Newton: University of Wisconsin-Madison
Christina Kendziorski: University of Wisconsin-Madison

Nature Communications, 2022, vol. 13, issue 1, 1-11

Abstract: Abstract Spatial transcriptomics is a powerful and widely used approach for profiling the gene expression landscape across a tissue with emerging applications in molecular medicine and tumor diagnostics. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind RNA. Ideally, unique molecular identifiers (UMIs) at a spot measure spot-specific expression, but this is often not the case in practice due to bleed from nearby spots, an artifact we refer to as spot swapping. To improve the power and precision of downstream analyses in spatial transcriptomics experiments, we propose SpotClean, a probabilistic model that adjusts for spot swapping to provide more accurate estimates of gene-specific UMI counts. SpotClean provides substantial improvements in marker gene analyses and in clustering, especially when tissue regions are not easily separated. As demonstrated in multiple studies of cancer, SpotClean improves tumor versus normal tissue delineation and improves tumor burden estimation thus increasing the potential for clinical and diagnostic applications of spatial transcriptomics technologies.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-022-30587-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30587-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-30587-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().