Identify agents impairing success across experiments.
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 install saboteurs
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.
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