NEWS.md

In FAST.R: Analyze and Visualize FAST-Generated Data

FAST.R 0.2.1

• Adjusted tuning parameters used for ML classifier training

FAST.R 0.2.0

• 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.

FAST.R 0.1.3

• 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.

FAST.R 0.1.2

FAST.R 0.1.1

FAST.R 0.1.0

• Initial CRAN submission.

FAST.R documentation built on June 22, 2024, 6:48 p.m.