TissueMiner is a framework to perform a multiscale analysis of an entire developing epithelium acquired at cellular resolution over several hours or days. It includes (a) tools to build a database from a timelapse movie, (b) ready-to-use tools to analyze various aspects of cell and tissue morphogenesis, and (c) a powerful but yet easy to use R programming interface to allow for the implementation of custom analyses.

• Installation
• Documentation

First, TissueMiner tracks cells in timelapse image series of a tissue and stores the results in a database. To do so, it uses TissueAnalyzer to segment and track cells in time and space.

Next, TissueMiner extracts and organizes information about cell geometry, topology (cell neighbor relationships) and ancestry from the TissueAnalyzer outputs into a database. By using sqlite, each movie is converted into a single database file.

TissueMiner comes along with a great variety of tools to work with the created movie database. These tools include

• Cell geometry analysis
• Cell topology analysis
• Cell lineage browsing
• Cell contributions to tissue deformation

Many of these tools provide tabular results as well as rendered movies to make the complex nature of timelapse more accessible.

TissueMiner provides a convenient R programming interface to query, quantify and visualize cell dynamics during epithelium morphogenesis in R. The functions provided with the TissueMiner API allow one to query the movie database for extracting quantities like:

• Cell state properties (position, area, anisotropy, cell packing geometry, fluorescence intensity)
• Rates and orientation of cellular events (divisions, cell neighbor changes, extrusions, shape changes)
• Rates of tissue deformation (area expansion and convergence-extension) contributed by each type of cellular event (tensorial description)

This API can then be employed to

• Visualize quantified data in graphs or directly on the movie images
• Do statistics (distribution of cell area, anisotropy, packing, bond length, vertex multiplicity, ...)
• Synchronize different movies in time
• Compare values between multiple movies and ROI's
• Do multiscale quantification and visualization using both tracked ROI's (Lagrangian description) and fixed grids (Eulerian description)

TissueMiner ships with a command-line Ubuntu-Installer and can be used via Docker on other platforms.

• To install TissueMiner on Ubuntu simply copy-paste the commands in the box below into a terminal to perform the following steps:
  • Define the directory where to install TissueMiner
  • Download TissueMiner repository (~120MB)
  • Install TM (~30 min due to the compilation of the source code of R packages)

# Step1
export TM_HOME="${HOME}/tissue_miner"
sudo apt-get update && sudo apt-get install git

# Step 2
git clone https://github.com/mpicbg-scicomp/tissue_miner.git ${TM_HOME}
${TM_HOME}/installation/ubuntu/install_tm.sh
source ${HOME}/.bashrc

• To update TissueMiner on Ubuntu, click here

• To install TissueMiner on a MacOS or a Windows system, we provide a Docker container that bundles TissueMiner and all its dependencies. If not yet present on your system, you need to install the docker toolbox beforehand (180Mb). On any non-Ubuntu Linux, please install the docker engine.

• Next, you can download the TissueMiner application bundled in a docker image called etournay/tissue_miner (~700Mb).

  • On Mac or Windows, open a Docker Quick Start Terminal:

docker pull etournay/tissue_miner

• For troubleshooting in case of out-of-date operating systems click here.

• To update TissueMiner, click here

• First install TissueMiner on your system.

• To get started with TissueMiner we suggest to do Quickstart Tutorials on our example data:

  • Quickstart TM-R Tutorials (Ubuntu).
  • Quickstart docker-TM-R Tutorials (Mac, Windows, other Linux).

• To get started with your own data analysis:

  • TM-R Tutorials (Ubuntu).
  • docker-TM-R Tutorials (Mac, Windows, other Linux).

• We provide the streamlined R scripts that are used in the tutorials to perform a simple analysis of a single movie. This includes a script entitled analyse_movie.R that performs most of the analyses described in the Quickstart Tutorials.

• We also provide an exhaustive TM R User Manual with lots of examples, background information and API details:

  • learn the necessary basics of the R language for TissueMiner (also see here)
  • learn the powerful libraries of TissueMiner for epithelium analysis
  • benefit from lots of examples to make your own scripts

• You already know Python and you like to use it instead ? We also provide a Tutorial in Python

• For a more general overview consider our Resource Paper.

• Commonly asked questions are answered in the FAQ section.

We provide four datasets:

• 1 demo sample (~35 Mb) to run Quickstart TM-R Tutorials

# In your unix terminal (or Docker QuickStart Terminal), type in:
curl https://cloud.mpi-cbg.de/index.php/s/vC0VqD2Wy4A6uqu/download  | tar -zxvf -

• 3 big datasets (~800Mb each) to explore more advanced capabilities of TissueMiner described in the TM R User Manual

# In your unix terminal (or Docker QuickStart Terminal), type in:

# Dataset WT_1 (~800Mb)
curl https://cloud.mpi-cbg.de/index.php/s/SgxxQk5CkIpTLPW/download  | tar -zxvf -

# Dataset WT_2 (~800Mb)
curl https://cloud.mpi-cbg.de/index.php/s/Z6ZR1b0sGWnC8Cj/download  | tar -zxvf -

# Dataset WT_3 (~600Mb)
curl https://cloud.mpi-cbg.de/index.php/s/4BJiyxnCS7HFyKB/download  | tar -zxvf -

Please use the github ticket system to report issues or suggestions. We also welcome pull requests.

If you like to use TissuMiner for your own research, please cite

Etournay et al. (2015). Interplay of cell dynamics and epithelial tension during morphogenesis of the Drosophila pupal wing. eLife, 4, e07090. doi:10.7554/eLife.07090