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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. 

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According to the Monocle 3 authors, you may want to filter in the top 5,000 genes with the highest variance (2,000 genes for datasets with fewer than 5,000 cells, and 300 genes for datasets with fewer than 1,000 cells) ⁽¹⁾. Those number should be used as a guidance for the first-pass analysis and may need to be optimized, depending on the project at hand and the biological question.

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To run Trajectory analysis tool, select the Normalized counts data node (or equivalent) and go to the toolbox: Exploratory analysis > Trajectory analysis

There These configuration dialog presents two options.

1. Dimensionality of reduced space. This option specifies the number of UMAP dimensions that the original data are reduced to, in order to learn the trajectory tree (dimensionality of original data equals the number of genes). Default is two, meaning that the trajectory plot will be draw in two dimensions. To get a 3D trajectory plot, increase this option to 3.
2. Scaling. Normalized expression values can be further transformed by scaling to unit variance and zero mean (i.e. converting to Z score). The use of this option is recommended ⁽¹⁾.

Under the hood, Monocle 3 will perform log2 transformation of the gene count matrix, scale the matrix (if selected), and project the gene count matrix into the top 50 principal components. Next, the dimensionality reduction will be implemented by UMAP (using default settings of the reduce_dimension command).

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