Data and analytical code for Allaway et al.
Written by: Casey S. Greene, Robert J. Allaway, and Balint Z. Kacsoh
In Vitro Immunofluorescence Intensity Analyses
See the manuscript for details on preparation, labeling, etc. After labeling measurement was performed in Fiji. The region was selected in the DAPI channel. Each measured region was paired with an adjacent background region. The source code begins with these data (measurements and background are on alternating) lines. Source code in combine_lines.py generates a summarized data table that includes background subtracted intensity values.
Plotting and analysis are performed via plot_cells.R.
Our goal was to examine the total intensity of fluorescence per unit area. Because we're going to divide these two items, we want to make sure that a decrease in cell size after treatment, or some other similar effect is not driving observed changes across treatments or replicates. The figures shown here merge replicates, but identical diagnostic figures faceted by replicates are included as _facet in the repository.
We examined area across conditions.
If we think that this is due to fluorescence intensity we should see differences in intensity across treatments, and we do.
We also plotted bivariate relationships with each treatment to identify potential issues and everything looks fine here too.
We performed a number of analyses to examine potential changes in the form of the distribution (e.g. two fluorescence populations with a shift) and did not observe this (diagnostic figures in the figures/cells folder), so we showed a boxplot with notches as the summary figure:
FNA-PDX Growth Curves During Dinaciclib Treatment
See the manuscript for details on the generation and characterization of the FNA-PDX models. Models were treated as described in the paper with Dinaciclib or vehicle control. Data are provided in raw-data/008-volumes.txt and raw-data/018-volumes.txt. Data are aggregated by process_volumes.py, and plotted by graph_volumes.R.
We performed LOESS regression and calculated 95% confidence intervals. Growth curves are calculated for both FNA models as well as a patient matched models of metastases. The vehicle control is shown in red, while the Dinaciclib treated models are shown in blue.
We also generated figures using the traditional (mean +/- standard error) approach, and these are shown below.
FNA-PDX Mean +/- SE:
Metastatic Models Mean +/- SE: