Plot the budding curves before alignment using the Python utility function by entering the command into a new cell. Next, plot the budding curves after alignment. Using the Python utility function.
Use the provided plot line graph comparison in the Python utilities vial to perform line graph comparisons on the original, aligned or aligned and interpolated data frame. By typing the command into a new cell, import a CSV or TSV gene list file into the notebook using the command in a new cell. Next, use the provided function plot heat map comparison in the Python utilities file to perform a heat map comparison on the aligned interpolated and phase aligned data frame by typing the command into a new cell.
A comparison of the aligned and unaligned transcriptomatic data showed that before alignment the first peak expression of the microarray experiments appeared aligned with the second peak of the RNA-seq Experiment. However, after alignment, the first cell cycle peaks of each dataset are appropriately aligned. Comparison of the cell cycle phase data across experiments with varying periods exhibited visible period differences in the unaligned budding curves.
Whereas clocks alignment made the three curves look remarkably similar, making comparisons of experimental data possible, the cell cycle phase data for each comparable lifeline point was not identical between the two conditions. Comparison of the transcriptomic data across experiments with varying periods showed that before alignment the transcript dynamics of CDC20 were non-overlapping. But after alignment, the peaks occurred on the same cell cycle phase but the shapes of the curves were different.
The genes were plotted as heat maps in the same order for all three conditions for both unaligned and aligned.
