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Added a new machine learning random forest classifier approach to distinguish between senescent and non-senescent cells based on the markers measured (SA-B-Gal, EdU, and Nuclear Area). This additional analysis can be easily performed by modifying the input metadata as described in the app.
Added a new tab, ‘Example Data’, which allows users to download example data. Such data can be used to test the FAST.R app or can serve as a benchmark to ensure your own data is structured correctly and ready for analysis.
Fixed FAST.R(Browser = FALSE) to correctly open the
app in a new RStudio window
Added a ‘Download all graphs’ button in the Data Visualization tab. This allows to download all graphs generated at once in a zip file.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.