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Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell trans...

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Detalles Bibliográficos
Autores principales: Chen, Huidong, Albergante, Luca, Hsu, Jonathan Y., Lareau, Caleb A., Lo Bosco, Giosuè, Guan, Jihong, Zhou, Shuigeng, Gorban, Alexander N., Bauer, Daniel E., Aryee, Martin J., Langenau, David M., Zinovyev, Andrei, Buenrostro, Jason D., Yuan, Guo-Cheng, Pinello, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478907/
https://www.ncbi.nlm.nih.gov/pubmed/31015418
http://dx.doi.org/10.1038/s41467-019-09670-4
Descripción
Sumario:Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell technologies. We further demonstrate its utility for understanding myoblast differentiation and disentangling known heterogeneity in hematopoiesis for different organisms. STREAM is an open-source software package.