ReadMe.md

Tissue To Cells

This repository contains methods used for discribing spatial distribution of myosin within and outside a cell in 2D epithelial tissue. [Bhide et al.]

These scripts/notebooks use output files from tissue analyzer.

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Requirements:

• Membrane segmentation results
• If tracking information is available then need the track_id_cells and local_id_cells information represented in the segmentation result

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For row-by-row analysis:

• Need cell ids belonging to every cell group/ cell row as a list. Enter it in the notebook tissues2Cells.ipynb

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For myosin inside vs myosin outside analysis (Figures 2K and 2L in the manuscript):

• Raw data (intensities) named as Img{i}_SUM.tif (e.g. Img5_SUM.tif)
• Membrane segmentation results as a folder Img{i}_segmentation with each segmented frame stored as a separate file cell_identity_T{i}.tif (e.g. cell_identity_T0.tif)
• Cell tracking results named img{i}.csv necessarily containing columns frame_nb, track_id_cells and local_id_cells

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Usage:

• Combine the datafile into HDF5 file using 'convert_tiffs.py'
• Run the notebook tissue2cells.ipynb and plot_myo_in_out.ipynb for analysis and measurement of myosin signal