The growing appetite of behavioral neuroscience for automated data production is prompting the need for new computational standards allowing improved interoperability, reproducibility, and shareability. We show here how these issues can be solved by repurposing existing genomic formats whose structure perfectly supports the handling of time series. This allows existing genomic analysis and visualization tools to be deployed onto behavioral data. As a proof of principle, we implemented the conversion procedure in Pergola, an open source software, and used genomics tools to reproduce results obtained in mouse, fly, and worm. We also show how common genomics techniques such as principal component analysis, hidden Markov modeling, and volcano plots can be deployed on the reformatted behavioral data. These analyses are easy to share because they depend on the scripting of public software. They are also easy to reproduce thanks to their integration within Nextflow, a workflow manager using containerized software.

We acknowledge the support of the “Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat i del Fons Social Europeu,” Spanish Ministry of Economy, Industry and Competitiveness (MEIC) under grant numbers BFU2014-55062-P and BFU2017-88264-P, the EMBL partnership, FEDER, the “Centro de Excelencia Severo Ochoa” Programme, and the CERCA Programme/Generalitat de Catalunya. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 635290-PanCanRisk and OpenRiskNet_731076. This reflects only the author's view and the funder is not responsible for any use that may be made of the information it contains. M.D. is supported by DIUE de la Generalitat de Catalunya (Grups consolidats SGR 2017/926), the Fondation Jérôme Lejeune (Paris, France), MINECO (SAF2013-49129-C2-1-R; SAF2016-79956-R), CDTI (“Smartfoods”) and EU (EraNet Neuron PCIN-2013-060 and JPND AC17/00006), and the Catalan foundation “La Marató de TV3” (#2016/20-30). The CIBER of Rare Diseases is an initiative of the ISCIII.