Extended Data Fig. 2: Q-PHAST graphical user interface.

a, Pipeline initialization command and initial graphical window for operating system (OS) selection. b, Window to choose the docker image to be used; at launch only version 1 is available. This window will allow users to choose among the installed Q-PHAST docker images. c, Folder selection window where the ‘input’ folder is selected and where you want the ‘output’ folder with all the results to be created. Click the ‘Run’ button to proceed to the next screen. d, Optional parameter settings. Adjust the experiment duration, commonly set at 24 h but adaptable on the basis of experimental requirements. Experimental images provided should have been acquired at this duration or longer. In addition, you can set the minimum nAUC value (raw fitness estimate) that is required for a spot to be considered growing, crucial for susceptibility analysis. Lastly, the ‘enhance contrast’ configuration improves image quality for optimal software performance. However, this may also be deactivated by setting ‘enhance contrast’ to ‘False’, which could be useful if the analyzed images have sufficient contrast and the default parameters yield poor results (this may be assessed by empirically looking at the pipeline’s outputs). e, Option for verification of spot coordinates and bad spots. Choose ‘Yes’ for reliable results, where the user is asked to verify the coordinates of all plates and the bad spots. The ‘No’ option performs these steps automatically and is recommended only for testing and development purposes. f, Definition of spot coordinates. Select the first spot (top left) and the last (bottom right) by clicking with the mouse and pressing ‘Enter’. To repeat the selection, double-click. Accurate identification of these spots is necessary for subsequent definition of the coordinates. g, Verification of spot coordinates. Press ‘Y’ (Yes) to accept verification and ‘N’ (No) to reject. If rejected, you will return to the step of defining coordinates (see f). h, Verification of predicted bad spots. The software identifies as ‘bad spots’ those that are outliers within the fitness distribution of different replicates of a given strain. For each strain in a given plate plate, we considered Q1 (first quartile), Q3 (third quartile) and IQR (interquartile range, Q3 − Q1) of the nAUC values across technical replicates. Potential ‘bad spots’ are defined as those that are outside of the range (Q1 − 2.5 × IQR, Q3 + 2.5 × IQR). An informative window displays three images summarizing spot growth on the plate, highlighting potential bad spots in a red box and their replicates in black. Growth curves are also shown in red for the potential bad spot and in black for its replicates. Identify the potential bad spot as bad by pressing ‘b’ or as good by pressing ‘g’. Bad spots will be excluded from future calculations and reflected in ‘extended_outputs’ in ‘bad_spot.xlsx’. I, Terminal showing the log of the pipeline. At the beginning, the complete execution code will be presented for reproducibility. This information will also be available in the folder ‘extended_outputs’. At any point in the process, you can see which step the pipeline is in, and upon completion, you will find a ‘success’ message and the time taken to complete the process.