To begin, activate the Conda environment by entering the command into the terminal. Use the command to open an interactive Python notebook. Create a new Python notebook in the desired folder, providing an appropriate name.
Then import the Python file containing the alignment functions by running the command in the first cell. If using budding data as the cell cycle phase data. Import a data frame containing the percent budded at each time point by running the command in a new cell.
Then align the budding data to a lifeline point timescale by entering the function into a new cell. Next, import the experimental data frame into the notebook by running the command in a new cell. Align the experimental data to a lifeline time point scale by entering the function into a new cell.
Then enter the command into a new cell to download the lifeline aligned data set. The budding data collected from the Condition 2 RNAseq showed the percent butted over time for both the unaligned timescale in minutes, and the aligned timescale in lifeline points. The flow cytometry data collected for the Condition 2 dataset plotted for a selected time points showed that the data matched the phase determined by the alignment.
