article Open AccessTop 1% cited
Reversed graph embedding resolves complex single-cell trajectories
Nature Methods · 2017 · Vol. 14(10) · pp. 979–982
Xiaojie Qiu✉(University of Washington)Qi MaoYing Tang(Shanghai Jiao Tong University)Li Wang(University of Illinois Chicago)Raghav Chawla(University of Washington)Hannah A. Pliner(University of Washington)Cole Trapnell(University of Washington)
Single-cell and spatial transcriptomicsCancer Genomics and DiagnosticsGene Regulatory Network AnalysisEmbeddingGraph embeddingComputational biologyCell fate determinationGraphComputer scienceBiologyGeneTranscription factorLineage (genetic)
Citations
5,149
FWCI
95.37
field-weighted impact
References
26
Percentile
100%
vs. same field & year
Citations per year
Cited by
Comprehensive Integration of Single-Cell Data
Cell · 2019 · 16,351 citations
The Major Risk Factors for Alzheimer’s Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ Plaques
Cell Reports · 2019 · 950 citations
SCANPY: large-scale single-cell gene expression data analysis
Genome biology · 2018 · 8,867 citations
Dictionary learning for integrative, multimodal and scalable single-cell analysis
Nature Biotechnology · 2023 · 4,189 citations
Eleven grand challenges in single-cell data science
Genome biology · 2020 · 1,379 citations
References
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Nature Biotechnology · 2014 · 7,571 citations
Objective Criteria for the Evaluation of Clustering Methods
Journal of the American Statistical Association · 1971 · 5,849 citations
Single-cell mRNA quantification and differential analysis with Census
Nature Methods · 2017 · 2,084 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.