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Trajectory analysis by Monocle 3 requires data normalisation normalization and preprocessing. We suggest to run the Recommended normalization from the Regarding the normalization, we suggest to first use the Normalization and scaling section of the toolbox (i.e. to normalize by counts per million (CPM), and add offset of 1, and then log2 transform). . After that, launch the Trajectory analysis on the Normalized counts node.

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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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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