The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Embracing the dropouts in single-cell RNA-seq analysis
Open accessAbstract
One primary reason that makes single-cell RNA-seq analysis challenging is dropouts, where the data only captures a small fraction of the transcriptome of each cell. Almost all computational algorithms developed for single-cell RNA-seq adopted gene selection, dimension reduction or imputation to address the dropouts. Here, an opposite view is explored. Instead of treating dropouts as a problem to be fixed, we embrace it as a useful signal. We represent the dropout pattern by binarizing single-cell RNA-seq count data, and present a co-occurrence clustering algorithm to cluster cells based on the dropout pattern. We demonstrate in multiple published datasets that the binary dropout pattern is as informative as the quantitative expression of highly variable genes for the purpose of identifying cell types. We expect that recognizing the utility of dropouts provides an alternative direction for developing computational algorithms for single-cell RNA-seq analysis.
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Cited by
He, S., Bhatt, R., Brown, C., Brown, E. A., Buhr, D. L., Chantranuvatana, K., Danaher, P., Dunaway, D., Garrison, R. G., Geiss, G., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01483-z · Cited by 814
Yang, F., Wang, W., Wang, F., Fang, Y., Tang, D., Huang, J., Lu, H., & Yao, J. (2021) · doi:10.1101/2021.12.05.471261 · Cited by 617
Statistics or biology: the zero-inflation controversy about scRNA-seq data
Jiang, R., Sun, T., Song, D., & Li, J. J. (2022) · Genome Biology · doi:10.1186/s13059-022-02601-5 · Cited by 614
Clearance of senescent macrophages ameliorates tumorigenesis in KRAS-driven lung cancer
Haston, S., Gonzalez-Gualda, E., Morsli, S., Ge, J., Reen, V., Calderwood, A., Moutsopoulos, I., Panousopoulos, L., Deletic, P., Carreno, G., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.05.004 · Cited by 251
Sarkar, A., & Stephens, M. (2021) · Nature Genetics · doi:10.1038/s41588-021-00873-4 · Cited by 224
Metadata
- Authors
- Qiu, P.
- Venue
- Nature Communications
- Published
- 2020-03-03
- Volume
- 11
- Issue
- 1
- Pages
- 1169-1169
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3009609875
- Cited by
- 391
- References
- 49
- FWCI
- 13.83
- Type
- journal article
- Language
- en
- Open access
- gold
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