GiniClust: detecting rare cell types from single-cell gene expression data with Gini index-Reference-Cited by-同舟云学术

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GiniClust: detecting rare cell types from single-cell gene expression data with Gini index

Published:2016-07-01 Issue:1 Volume:17 Page:
ISSN:1474-760X
Container-title:Genome Biology
language:en
Short-container-title:Genome Biol

Author:

Jiang Lan,Chen Huidong,Pinello Luca,Yuan Guo-Cheng

Funder

National Heart, Lung, and Blood Institute

Claudia Barr Award

National Human Genome Research Institute

Publisher

Springer Science and Business Media LLC

Link

http://link.springer.com/content/pdf/10.1186/s13059-016-1010-4.pdf

Reference28 articles.

1. Lukk M, Kapushesky M, Nikkila J, Parkinson H, Goncalves A, Huber W, et al. A global map of human gene expression. Nat Biotechnol. 2010;28:322–4.

2. Saadatpour A, Lai S, Guo G, Yuan GC. Single-cell analysis in cancer genomics. Trends Genet. 2015;31:576–86.

3. Stegle O, Teichmann SA, Marioni JC. Computational and analytical challenges in single-cell transcriptomics. Nat Rev Genet. 2015;16:133–45.

4. Zeisel A, Munoz-Manchado AB, Codeluppi S, Lonnerberg P, La Manno G, Jureus A, et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science. 2015;347:1138–42.

5. Wilson NK, Kent DG, Buettner F, Shehata M, Macaulay IC, Calero-Nieto FJ, et al. Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations. Cell Stem Cell. 2015;16:712–24.

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