Number of neighbors. This user defined setting determines the number of approximate nearest neighbors used to create the initial high-dimension graph.

Number of neighbors is a crucial parameter as low values will instruct the UMAP algorithm to focus more on local structure by constraining the number of neighboring points considered when analyzing the data in high dimensions, while high values will instruct the UMAP algorithm towards representing the overall structure while sacrificing fine detail.

Min Low Dim Distance sets the Minimum Distance between points in the low-dimensional map (i.e. in the UMAP map). By setting low values, points will be clustered closer together.  By setting high values, points will be clustered loosely together.

For more details on UMAP algorithm used in FCS Express, please refer to the following resources:

* Leland McInnes et al. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. 2018 arXiv:1802.03426

* Becht E. et al. Dimensionality reduction for visualizing single-cell data using UMAP Nat Biotechnol. 2018;10.1038

* Andy Coenen, Adam Pearce. Understanding UMAP.

To get started we have a short video on creating a UMAP in FCS Express that can be reviewed.

For additional information about using UMAP from our manual, please click here.