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non machine learning model tool

for machine learning model tool for passage variability -

Python and R specific

Dynamic Passage Variability Test Tool (PAVATE)

non machine learning model tool

Analyze variability in cell culture data across multiple passages. Input cell counts, viability, doubling times, confluence percentages, and additional features to calculate key statistics and visualize trends. The tool offers:

  • Coefficient of Variation

  • Correlations

  • Cosine Similarities

  • Z-Scores

  • Normalized Values

Visualize your data with an interactive line chart for comprehensive insights.

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