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NEUBIAS2018 Szeged TS7 High Content Screening.md

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High Content Image Data Screening and Analysis

Author

Csaba Molnar, BIOMAG Group, Biological Research Centre, Szeged

Abstract

In this workshop we aim to implement an image-based analysis of a biological system by profiling the phenotipic response of a cancer cell line following perturbation with a small-molecule compound library. (...being extended...)

Software Installation

All the following softwares are recommended to be installed by the time of the TS.

Required softwares:

  • Matlab R2015b or newer version with Image Processing Toolbox, Statistics and Machine Learning Toolbox, and Bioinformatics Toolbox
    • Demo licences for Matlab R2017b are provided during the Training School TS7.
    • The participants who applied for demo licences get the location and installation guide via e-mail from the hungarian distributor of Matlab.
    • Installation guide is available here
    • The demo licence packages contain all the necessary toolboxes.
    • Note: old laptops and computer with 32-bit processors are not capable of running this newest version of Matlab. For those who has 32-bit workstations the R2015b version is required, but they should state their demo licence demand separately!
  • CellProfiler 2.2.0
    • Download CellProfiler 2.2.0 release from here.
    • Be aware of non-English characters in the path of your home directory! If you have those, you have to change the plugin directory by editing registry.
  • Advanced Cell Classifier
    • Download ACC 3.0 from here. You can use Win standalone version, or you can run it's source code in Matlab.
    • Download ExportToACC CellProfiler module for saving data in ACC format. Copy exporttoacc.py file into the CellProfiler's plugins directory (File->Preferences->CellProfiler plugins directory).

Sample Data

  • Approximate total size of sample data set: ~2GB raw data -> ~10GB in total
  • Capturing conditions
    • organism: human MCF-7 breast cancer cells
    • labeled: DNA (DAPI), F-actin (Phalloidin) and B-tubulin (anti–β-tubulin antibody)
    • microscopy: fluorescent, ImageXpress 5000A high-content imaging platform (Molecular Devices), ×20 PanFluor ELWD Ph1 DM objective, 16-bit camera binning resolution of 1
    • spatial resolution: 0.5μm
    • time resolution [dt]: -.
  • Location: will be locally distributed in the school

Resources

References