Iterative single-cell multi-omic integration using online learning-Reference-Cited by-同舟云学术

Iterative single-cell multi-omic integration using online learning

Published:2021-04-19 Issue:8 Volume:39 Page:1000-1007
ISSN:1087-0156
Container-title:Nature Biotechnology
language:en
Short-container-title:Nat Biotechnol

Author:

Gao Chao^ORCID,Liu Jialin,Kriebel April R.,Preissl Sebastian^ORCID,Luo Chongyuan,Castanon Rosa,Sandoval Justin,Rivkin Angeline,Nery Joseph R.^ORCID,Behrens Margarita M.,Ecker Joseph R.^ORCID,Ren Bing,Welch Joshua D.^ORCID

Funder

U.S. Department of Health & Human Services | NIH | National Institute of Mental Health

U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute

Division of Intramural Research, National Institute of Allergy and Infectious Diseases

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,Molecular Medicine,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://www.nature.com/articles/s41587-021-00867-x.pdf

Reference33 articles.

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3. Stuart, T. & Satija, R. Integrative single-cell analysis. Nat. Rev. Genet. 20, 257–272 (2019).

4. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

5. Welch, J. D. et al. Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell 177, 1873–1887 (2019).

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