BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis
Agency for Science, Technology and Research · Genome Institute of Singapore · +7 more institutions
Abstract
Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can…
Citation impact
- FWCI
- 45.62
- Percentile
- 100%
- References
- 84
Authors
13- VSVipul Singhal
Agency for Science, Technology and Research, Genome Institute of Singapore
- NCNigel Chou
Agency for Science, Technology and Research, Genome Institute of Singapore
- JLJoseph Lee
National University of Singapore
- YYYifei Yue
National University of Singapore
- JLJinyue Liu
Agency for Science, Technology and Research, Genome Institute of Singapore
Topics & keywords
- Biology
- Computational biology
- Segmentation
- Domain (mathematical analysis)
- Scalability
- Spatial analysis
- Evolutionary biology
- Computer science
- Sustainable cities and communities
Funding
- NRNational Research Foundation
- AFAgency for Science, Technology and ResearchAwards: #H18/01/a0/020, I1801E0029, 202D800010
- NRNational Research Foundation SingaporeAward: NRF-CRP25-2020-0001
- MRMedical Research Council
- NMNational Medical Research CouncilAwards: OF-YIRG18nov-0014, NRF-CRP25-2020-0001, OFIRG21jun-0090, OFIRG-000618-00, OFIRG20nov-0056
- GTGraduiertenakademie, Technische Universität Dresden