Instructions of Code Usage

This is a collection of customized scripts (Jupyter notebook, R, ImageJ macro and Jython) used for image analysis, plotting and movie making in Wang et al., 2021.

The source data for using these scripts can be downloaded here. The scripts and data should be placed in the same directory so that the relative path in the scripts can be direclty used.

Please kindly cite our paper if you used them in your work.

---

Image analysis and plotting

Refer to the table below for a guide of which scripts were used to generate the plot(s) of interest.

Figures	Scripts used
Fig. 1E	SMG-surface-cell-tracks-Imaris.ipynb
Fig. 1G-J	SMG-get-peripheral-line-profile-step1.ijm SMG-dynamic-peripheral-line-scan.ipynb SMG-get-peripheral-line-profile-step3.ijm
Fig. 2A	SMG-surface-cell-division-types.ipynb
Fig. 2B	SMG-post-division-return-time.ipynb
Fig. 2D	SMG-get-E-cadherin-surface-to-center-line-scan.ijm SMG-E-cad-line-scan-plotting.ipynb
Fig. 2F-G	SMG-get-E-cadherin-edge-AUC-peakHeight-by-line-scan.ijm SMG-E-cad-K14RFP-correlation.ipynb
Fig. 3B	count-buds.ijm SMG-bud-count-collagenase-recovery.ipynb
Fig. 3E	SMG-surface-cell-division-types.ipynb
Fig. 3F	SMG-post-division-return-time.ipynb SMG-surface-residence-ratio.ipynb
Fig. 3I	SMG-mesenchyme-1-draw-epithelial-ROIs.ijm SMG-mesenchyme-2-get-mesenchyme-DAPI-actin-images.ijm SMG-mesenchyme-cellpose-segmentation.ipynb SMG-mesenchyme-compute-and-plot-shape-metrics.ipynb
Fig. 3J	SMG-mesenchyme-cell-tracks-Imaris.ipynb
Fig. 3K	SMG-collagenase-compute-epi-and-mes-ROIs.ijm SMG-collagenase-get-pHH3-epi-mes-quantifications.ijm SMG-collagenase-pHH3-plotting.ipynb
Fig. 4A-E	E13epi-scRNA-seq-analysis.ipynb
Fig. 4F	E13epi-scRNA-seq-plotting.ipynb
Fig. 4H	SMG-Cdh1-smFISH-plotting.ipynb
Fig. 5C, F, G	count-buds.ijm SMG-bud-count-single-cell-single-bud-culture.ipynb
Fig. 5J	SMG-surface-cell-division-types.ipynb
Fig. 6D	count-buds.ijm DLD-1-spheroid-bud-count-decoding-plotting.ipynb
Fig. 6E-F	DLD-1-spheroid-curvature-analysis.ipynb
Fig. 7B, F, I, L	count-buds.ijm DLD-1-spheroid-bud-count-decoding-plotting.ipynb
Fig. 7C, G, J, M	DLD-1-spheroid-draw-interior.ijm < br> DLD-1-spheroid-protruded-area-decoding-plotting.ipynb
Fig. 7D	DLD-1-spheroid-curvature-analysis.ipynb
Fig. 7N	DLD-1-AFM-plotting.ipynb
Fig. S1E	SMG-epithelia-track-speed-Imaris.ipynb
Fig. S1F-M	SMG-get-peripheral-line-profile-step1.ijm SMG-dynamic-peripheral-line-scan.ipynb SMG-get-peripheral-line-profile-step3.ijm
Fig. S2C-E	SMG-live-draw-3d-ROIs-single-time-frame.ijm SMG-compute-3D-mesh.ipynb SMG-tracking-post-division-return-TrackMate.ipynb
Fig. S2F	SMG-time-course-pHH3-draw-and-compute-epi-ROIs.ijm SMG-time-course-pHH3-get-pHH3-surface-interior-quantifications.ijm SMG-time-course-pHH3-plotting.ipynb
Fig. S2L	Mathematical-modeling-pHH3-plotting.ipynb
Fig. S3A	count-buds.ijm SMG-bud-count-Ecad-integrin-blocking-antibody.ipynb
Fig. S3B	count-buds.ijm SMG-bud-count-collagenase-titration.ipynb
Fig. S3D	count-buds.ijm SMG-bud-count-BB94-GM6001.ipynb
Fig. S4A	E13epi-scRNA-seq-analysis.ipynb
Fig. S4E	E13epi-scRNA-seq-plotting.ipynb
Fig. S5D, F	DLD-1-cell-get-mean-intensity-Ecad-D193-D266-D267.ijm DLD-1-cell-get-background-intensity-Ecad-D193-D266-D267.ijm DLD-1-cell-Western-blot-and-immunofluorescence-quantification.ipynb
Fig. S6B, D-F, I	count-buds.ijm DLD-1-spheroid-bud-count-decoding-plotting.ipynb DLD-1-spheroid-draw-interior.ijm DLD-1-spheroid-protruded-area-decoding-plotting.ipynb DLD-1-spheroid-curvature-analysis.ipynb
Fig. S7B, D	count-buds.ijm DLD-1-spheroid-bud-count-decoding-plotting.ipynb DLD-1-spheroid-draw-interior.ijm DLD-1-spheroid-protruded-area-decoding-plotting.ipynb
Fig. S7F	DLD-1-cell-get-mean-intensity-b1integrin-and-Ecad-D193-D301-D304.ijm DLD-1-cell-get-background-intensity-b1integrin-and-Ecad-D193-D301-D304.ijm DLD-1-cell-Western-blot-and-immunofluorescence-quantification.ipynb
Fig. S7K-L	DLD-1-cell-count-cells-attachment-assay.ijm DLD-1-cell-attachment-assay.ipynb
Fig. S7N	DLD-1-AFM-plotting.ipynb

---

Making and annotating videos

• Image sequences of automated surface rendering and cell tracking were generated in Imaris 9.5.0 (Bitplane). All other image sequences were generated in Fiji.

  • Tracking of daughter cells from surface-derived cell divisions (Movie S7) was performed using TrackMate, a Fiji plugin. Images of tracked cells were exported using the Jython script "TrackMate-tracking-export-spot-tif-series.py" running in Fiji. Exported image sequences of individual cell tracks were assembled and formatted using ImageJ macro scripts "TrackMate-tracking-save-exported-series-as-stack.ijm" and "TrackMate-tracking-equalize-frames-of-merged-spot-stacks.ijm".

• Image stacks were annotated using "movie-annotation-add-time-stamp.ijm", "movie-annotation-add-scale-bar.ijm" and "movie-annotation-add-arrows-time-lapse-frames.ijm" before or after being combined or concatenated into a single image stack for a single video.

  • Note, make sure the image width and height pixel sizes are even numbers, otherwise ffmpeg may complain.

• Annotated image stacks were exported to tif image sequences and made into H.264 encoded mp4 videos using "make-movie.py", which is a Python wrapper of ffmpeg.

  usage: python make-movie.py [-h] folder fps target_size [n_digit_ImgID] [quality]
  
  positional arguments:
    folder         folder containing the image sequence for movie making
    fps            playback speed in frames per second
    target_size    the desired file size in MB
    n_digit_ImgID  optional; the digit number of image IDs of the image
                   sequence; default 4
    quality        optional; quality, 0 highest, 63 lowest; default 0
  
  optional arguments:
    -h, --help     show this help message and exit

  For example, the following command makes the image sequence stored in '~/branching-paper/movie-1' into a '.mp4' movie at 12 fps and with a file size under 15 MB. The movie is saved in the parental folder of the image sequence folder ('~/branching-paper/'):

  python make-movie.py ~/branching-paper/movie-1 12 15