Abstract
In many single-cell RNA-seq (scRNA-seq) experiments, cells represent progressively changing states along a continuous biological process. A useful approach to analyzing data from such experiments is to computationally order cells based on their gradual transition of gene expression. The ordered cells can be viewed as samples drawn from a pseudo-temporal trajectory. Analyzing gene expression dynamics along the pseudotime provides a valuable tool for reconstructing the underlying biological process and generating biological insights. TSCAN is an R package to support in silico reconstruction of cells’ pseudotime. This chapter introduces how to apply TSCAN to scRNA-seq data to perform pseudotime analysis.
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Ji, Z., Ji, H. (2019). Pseudotime Reconstruction Using TSCAN. In: Yuan, GC. (eds) Computational Methods for Single-Cell Data Analysis. Methods in Molecular Biology, vol 1935. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9057-3_8
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DOI: https://doi.org/10.1007/978-1-4939-9057-3_8
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