How to optimize ICM (Illumina Connected Multiomics) Data Viewer Performance

Data processed by Illumina Connected Multiomics can be highly dimensional. File formats like sparse matrix files can help to condense the data for portability and accessibility. While file size can play a factor in loading times, additional factors such as the data content (e.g the total number of cells or the total number of genes/features) can result in extended loading times when attempting to visualize the data.

To improve visualization loading times, it is recommend to perform filtering to ensure only the desired data is selected. For example, removing any cells with <400 counts excludes potential noise and results in a smaller dataset to load and visualize.

Each dataset can have different considerations, so the optimal settings and value may need to be empirically derived.

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