DC3 is a method for deconvolution and coupled clustering from bulk and single-cell genomics data

Wanwen Zeng; Xi Chen; Zhana Duren; Yong Wang; Rui Jiang; Wing Hung Wong

doi:10.1038/s41467-019-12547-1

Nature Communications (Oct 2019)

DC3 is a method for deconvolution and coupled clustering from bulk and single-cell genomics data

Wanwen Zeng,
Xi Chen,
Zhana Duren,
Yong Wang,
Rui Jiang,
Wing Hung Wong

Affiliations

Wanwen Zeng: Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University
Xi Chen: Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University
Zhana Duren: Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University
Yong Wang: CEMS, NCMIS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Rui Jiang: MOE Key Laboratory of Bioinformatics, Bioinformatics Division, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University
Wing Hung Wong: Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University

DOI: https://doi.org/10.1038/s41467-019-12547-1
Journal volume & issue: Vol. 10, no. 1
pp. 1 – 11

Abstract

Read online

Single-cell omics analysis can reveal heterogeneity among individual cells at different levels. Here, the authors develop DC3, a computational method for joint analysis of various bulk and single-cell data from the same heterogeneous cell population.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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