Joint analysis of heterogeneous single-cell RNA-seq dataset collections

被引：174

作者：

Barkas, Nikolas ^{[1
]}

Petukhov, Viktor ^{[1
,2
]}

Nikolaeva, Daria ^{[1
]}

Lozinsky, Yaroslav ^{[1
]}

Demharter, Samuel ^{[2
]}

Khodosevich, Konstantin ^{[2
]}

Kharchenko, Peter V. ^{[1
,3
]}

机构：

[1] Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA

[2] Univ Copenhagen, Fac Hlth & Med Sci, Biotech Res & Innovat Ctr, Copenhagen, Denmark

[3] Harvard Stem Cell Inst, Cambridge, MA 02138 USA

来源：

NATURE METHODS | 2019年 / 16卷 / 08期

关键词：

ATLAS;

D O I：

10.1038/s41592-019-0466-z

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Single-cell RNA sequencing is often applied in study designs that include multiple individuals, conditions or tissues. To identify recurrent cell subpopulations in such heterogeneous collections, we developed Conos, an approach that relies on multiple plausible inter-sample mappings to construct a global graph connecting all measured cells. The graph enables identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.

引用

页码：695 / +

页数：7

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