The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
SpatialDWLS: accurate deconvolution of spatial transcriptomic data
Open accessPublished version of a preprint
Abstract
Recent development of spatial transcriptomic technologies has made it possible to characterize cellular heterogeneity with spatial information. However, the technology often does not have sufficient resolution to distinguish neighboring cell types. Here, we present spatialDWLS, to quantitatively estimate the cell-type composition at each spatial location. We benchmark the performance of spatialDWLS by comparing it with a number of existing deconvolution methods and find that spatialDWLS outperforms the other methods in terms of accuracy and speed. By applying spatialDWLS to a human developmental heart dataset, we observe striking spatial temporal changes of cell-type composition during development.
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Cites
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Cited by
Exploring tissue architecture using spatial transcriptomics
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Metadata
- Authors
- Dong, R., & Yuan, G.-C.
- Venue
- Genome Biology
- Published
- 2021-05-10
- Volume
- 22
- Issue
- 1
- Pages
- 145-145
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- OpenAlex
- W3161009639
- Cited by
- 304
- References
- 23
- FWCI
- 14.22
- Type
- journal article
- Language
- en
- Open access
- gold
- Licence
- creativecommons.org/licenses/by/4.0 (tdm)
- creativecommons.org/licenses/by/4.0 (vor)
- Funders
- NIH Office of the Director (UH3HL145609)
- National Institute on Aging (R01AG066028)
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