Skip to main content

Identify agents impairing success accross experiments.

Project description

Saboteurs is a Python library to detect bad elements (or weakest links) from success/failure data. It can also be used to design “test batches” which will allow to easily identify bad elements.

We use it at the Edinburgh Genome Foundry to identify defectuous genetic parts early:

  • When assembling large fragments of DNA, each with typically 5 to 25 parts, we observe that some assemblies have far fewer successes (“good clones”) than some others. We use Saboteurs to identify possible parts which would be causing the damage. This would generally mean that the sample corresponding to these parts has been compromised.
  • Before launching a large batch of assemblies which reuse the same few parts, we use Saboteurs to design a smaller “test batch” of carefully selected assemblies to detect and identify possible bad parts.


PIP installation:

pip install saboteurs


Github Page:

Web apps:

Saboteurs detection

Batch design

License: MIT, Copyright Edinburgh Genome Foundry

More biology software

Saboteurs is part of the EGF Codons synthetic biology software suite for DNA design, manufacturing and validation.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for saboteurs, version 0.3.2
Filename, size File type Python version Upload date Hashes
Filename, size saboteurs-0.3.2-py3-none-any.whl (40.5 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size saboteurs-0.3.2.tar.gz (44.8 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page