biPOD is a package to infer kinetic parameters of an evolving population whose size is observed at discrete intervals of time. The tool is able to:
- Infer growth rates and instant of birth of a population of cells
when time windows and change points are known. This includes:
- Calculating exponential growth rates for different time periods (e.g., treatment phase, relapse phase)
- Determining the upper limit for the population’s birth time if growth is observed in the initial window
- Handling multiple time windows with predefined change points
- Identify optimal change points in population dynamics when these
transition times are not known, by:
- Analyzing population size data to detect significant changes in growth patterns
- Computing the most likely moments when population behavior shifts
- Optimizing the placement of change points to best fit the observed data
- Analyze dual-population scenarios typical in treatment-to-relapse
cases, characterized by:
- Inferring separate growth rates for resistant and sensitive cell populations
- Determining the birth time of the resistant population
- Calculating the death time of the sensitive population
- Modeling the characteristic U-shaped dynamics that emerge from the interplay between these populations
If you use biPOD, please cite:
- G. Santacatterina, R. Bergamin, A. Zucchetto, R. Laureana, M.I. del Principe, V. Gattei, L. Egidi, G. Caravagna. Predicting tumour evolution and drug resistance from heterogenous longitudinal cancer data. biorxiv (2024).
# install.packages("devtools")
devtools::install_github("caravagnalab/biPOD")Cancer Data Science (CDS) Laboratory, University of Trieste, Italy.
