6 It has been shown that, in the context of genotype-phe- notype correlation with a large database, the linear model without interactions provided also accurate predictions [6]. However, based on the full dataset results, we highlight the importance of the two-way interactions terms for Least Squares. Interactions between mutations are of scientiﬁc interest, both to help in drug selection and to understand mechanisms of resistance. 6. Conclusion In this study, we showed that the Super Learner methodology applied on a relative small amount of data, provided good performance. Of note in our dataset, simple linear regression with two-way interaction terms performs as well as the Super Learner. Author’s Contribution A. Houssa¨ıni and P. Flandre designed research; A. Houssa¨ıni and P. Flandre performed analysis; A. Houssa¨ıni, L. Assoumou, A. G. Marcelin, J. M. Molina, V. Calvez and P. Flandre discussed the results and improved the paper. Disclosure P. Flandre has received travel Grant or consulting fees from Abbott, Bristol-Myers Squibb, Gilead, Janssen-Tibotec and ViiV Health Care. Dr. Molina has received travel Grant or consulting fees from Bristol-Myers Squibb. A. Houssa¨ıni, L. Assoumou, A. G. Marcelin and V. Calvez have none to declare. Acknowledgments The authors thank Bristol-Meyer Scribb (Dr. Yacia Bennai) for making the Jaguar study data available. A. Houssa¨ıni is grateful for the ﬁnancial support of SIDACTION in the form of a Ph. D. fellowship. This work was supported by SIDAC- TION Grant FJC-1/AO20-2/09, the Agence Nationale de Recherches sur le SIDA (ANRS), the European Community Seventh Framework Programme (FP7/2007–2013) under the project “Collaborative HIV and Anti-HIV Drug Resistance Network (CHAIN)”, grant agreement no. 223131, and ARVD (Association de Recherche en Virologie en Dermatologie). References [1] P. Lorenzi, M. Opravil, B. 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