ARTra: Additive and Replacing Transfer Inference

ARTra (short for “Additive and Replacing Transfer Inference”) is a program for inferring and distinguishing between additive and replacing horizontal gene transfer events. ARTra uses Duplication-Transfer-Loss (DTL) reconciliation to infer transfer events and then uses a trained machine learning classifier to classify the inferred transfers as additive or replacing. It also implements three simple non-machine-learning-based classification heuristics, including the “gene-frequency” heuristic described in the paper available from and implemented in the RANGER-DTL-RT tool. The other two heuristics, lost-gene heuristic and mapping-count heuristic, are described in the paper cited below. The machine learning classifier uses the classifications generated by these heuristics, along with some additional features, to generate an improved ensemble classification. Further technical details appear in the paper cited below.

ARTra was implemented by Abhijit Mondal and is available open-source under GNU GPL. Precompiled executables, source code, and a user manual are available below.

This software can be cited as follows:

Funding: Development of the software resource(s) available from this webpage was funded in part by U.S. National Science Foundation award MCB 1616514.

Contact: Please feel free to contact Abhijit Mondal ( or Mukul Bansal ( if you have any questions, concerns, or suggestions.