A collection of python tools for processing image-based RNAi screens.


Welcome to rnaiutilities.

rnaiutilities provide a set of python modules and commandline scripts that can be used to process, convert, query and analyse imaged-based RNAi-screens.

The packages are designed for the following workflow:

  • Download raw mat files from an openBIS instance or where ever your data lie. The mat files are supposed to be created by CellProfiler, i.e. platewise data-sets, where every file describes a single features for single-cells.
  • Parse the downloaded data using rnai-parse: install the package, and process as described in the package folder. This generates a list of raw tsv files or a bundled h5 file. Until now the parser writes featuresets for cells, perinuclei, nuclei, expandednuclei, bacteria and invasomes.
  • Query the meta DB using rnai-query and create and combine datasets. For that first meta files generated from the step above are written into a database. Then the DB can be queried against to subset single genes, sirnas, pathogens, etc. and write the normalized results.
  • To come: rnai-analyse for analysing large-scale RNAi screens.

The package is still under development, so if you’d like to contribute, fork us on GitHub.


Make sure to have python3 installed. rnaiutilities does not support previous versions. The best way to do that is to download anaconda and create a virtual environment.

Download the latest release first and install it using:

pip install .

If you get errors, I probably forgot some dependency.