What is UMAP?
Uniform Manifold Approximation and Projection, or UMAP, is a dimensionality reduction technique that allows users to create new UMAP X and UMAP Y parameters from a high-dimensional dataset.
UMAP is now available in FCS Express through its new Pipelines feature.
Advancements in cytometry have allowed for researchers to capture information for many different parameters on a single cell. Analyzing the complex high-dimensional single-cell data can present many challenges. Many algorithms have been created to assist in understanding and visualizing these data sets.
In FCS Express, we offer UMAP (Uniform Manifold Approximation and Projection) algorithm as a Pipeline step. UMAP is a dimensionality reduction technique that constructs a high dimensional graph representation of the data then creates a low-dimensional graph to be as structurally similar as possible. This results in the creation of two new parameters UMAP 1 and UMAP 2. UMAP captures local relationships within a cluster as well as global relationships between distinct clusters.
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:
FCS Express on Mac
Upgrading FCS Express