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Overview of Trajectory Analysis

Cells undergo changes to transition from one state to another as part of development, disease, and throughout life. Since those changes can be gradual, trajectory analysis attempts to describe progress through a biological process as a position along a path. Because biological processes are often complex, trajectory analysis builds branching trajectories where different paths can be chosen at different points along the trajectory. The progress of a cell along a trajectory from the starting point or root, can be quantified as a numeric value, pseudotime. 

In Partek Flow, we use tools from Monocle 3 [1] to build trajectories, identify states and branch points, and calculate pseudotime values. The output of Trajectory analysis task includes an interactive 2D/3D visualization for viewing the trajectory trees and setting the root states (starting points of the trajectories). From the Trajectory analysis report, you can run a second task, Calculate pseudotime, which adds a numeric cell-level attribute, Pseudotime, calculated using the chosen root states. 

Setting up Trajectory Analysis

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References

1. Cao J, Spielmann M, Qiu X, Huang X, Ibrahim DM, Hill AJ, Zhang F, Mundlos S, Christiansen L, Steemers FJ, Trapnell C, Shendure J. The single-cell transcriptional landscape of mammalian organogenesis. Nature. 2019 Feb;566(7745):496-502. doi: 10.1038/s41586-019-0969-x. Epub 2019 Feb 20. PMID: 30787437; PMCID: PMC6434952.

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