Latch Plots enable scientific teams to get faster and more reproducible results (e.g., standard curves, normalized fluorescence, cell gating) while freeing your bench team’s time for rote analysis of qPCR, plate readers, ELISA, and flow cytometry.

Latch Plots is currently in alpha release and confidential. Please do not share any details outside of your organization.


Wet lab teams currently use non-standard and labor-intensive workflows to understand data from plate-based biochemical assays. These workflows:

  1. Use different spreadsheet and file storage software (Google Sheets/Drive, Excel, DropBox, Sharepoint, Box)
  2. Are scattered on individual laptops
  3. Require bespoke spreadsheet calculations to e.g. transpose cells to match plate layouts, normalize values
  4. Involve manual clicking and user error in downstream native software like GraphPad, yielding different results between users with no traceability

Latch Plots

For bioinformaticians and developers:

  • Latch Plots provides an easy way to create data transformations in Python and expose user-friendly widget components that enable scientists to perform these transformations on their own.
  • With the versatility of Python, developers can create any data transformations that they want, from simple table operations (sort, rank, transpose) to complex statistical tests (outlier detection, non-linear curve fitting).

For scientists:

  • Access a plotting layout with intuitive, no-code steps to run data transformations and statistical tests
  • Creative interactive visualizations in a few clicks
  • Hover, zoom, pan, and lasso-select points to display the underlying data points

Next steps