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Fig. 1 | Stem Cell Research & Therapy

Fig. 1

From: Single-cell RNA sequencing to track novel perspectives in HSC heterogeneity

Fig. 1

Typical applications of single-cell RNA sequencing. A Identifying cell population. scRNA-Seq datasets are processed through dimension reduction techniques to ease visual evaluation. Molecular clustering enables the identification of heterogeneous cell subtypes and novel populations. Clusters can be further annotated by their gene expression characteristics. B Differentiation trajectory analysis. Pseudotime analysis basing on scRNA-Seq datasets orders single cell along the “time-series” axis that represents dynamic cell state transitions, such as differentiation or signaling responses to an external stimulus. On the cell developmental trajectories map, special genes that drive branching events can be highlighted. C Identifying transcription mechanics. Cell transcription state and candidate transcription factors can be exploited to guide the reconstruction of gene regulatory networks, which suggest critical insights into transcriptional dynamics and the mechanisms driving cellular heterogeneity

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