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Trajectory inference
From Wikipedia, the free encyclopedia
Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic process experienced by cells and then arrange cells based on their progression through the process. Single-cell protocols have much higher levels of noise than bulk RNA-seq,[1] so a common step in a single-cell transcriptomics workflow is the clustering of cells into subgroups.[2] Clustering can contend with this inherent variation by combining the signal from many cells, while allowing for the identification of cell types.[3] However, some differences in gene expression between cells are the result of dynamic processes such as the cell cycle, cell differentiation, or response to an external stimuli. Trajectory inference seeks to characterize such differences by placing cells along a continuous path that represents the evolution of the process rather than dividing cells into discrete clusters.[4] In some methods this is done by projecting cells onto an axis called pseudotime which represents the progression through the process.[5]
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