Please note that Monocle 2 has officially been deprecated and has been left in place for Partek Flow users with historical data. For any new analysis, please use Monocle 3.

What is trajectory analysis?

Cells undergo changes to transition from one state to another as part of development, disease, and throughout life. Because these 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 2 [1] to build trajectories, identify states and branch points, and calculate pseudotime values. The output of Trajectory analysis includes an interactive scatter plot visualization for viewing the trajectory and setting the root state (starting point of the trajectory) and adds a categorical cell level attribute, State. From the Trajectory analysis task report, you can run a second task, Calculate pseudotime, which adds a numeric cell-level attribute, Pseudotime, calculated using the chosen root state. Using the state and pseudotime attributes, you can perform downstream analysis to identify genes that change over pseudotime and characterize branch points. 

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