  Atmospheric characterisation of exoplanets from the ground is an actively
growing field of research. In this context we have created the ATMOSPHERIX
consortium: a research project aimed at characterizing exoplanets atmospheres
using ground-based high resolution spectroscopy. This paper presents the
publicly-available data analysis pipeline and demonstrates the robustness of
the recovered planetary parameters from synthetic data. Simulating planetary
transits using synthetic transmission spectra of a hot Jupiter that were
injected into real SPIRou observations of the non-transiting system Gl 15 A, we
show that our pipeline is successful at recovering the planetary signal and
input atmospheric parameters. We also introduce a deep learning algorithm to
optimise data reduction which proves to be a reliable, alternative tool to the
commonly used principal component analysis. We estimate the level of
uncertainties and possible biases when retrieving parameters such as
temperature and composition and hence the level of confidence in the case of
retrieval from real data. Finally, we apply our pipeline onto two real transits
of HD~189733 b observed with SPIRou and obtain similar results than in the
literature. In summary, we have developed a publicly available and robust
pipeline for the forthcoming studies of the targets to be observed in the
framework of the ATMOSPHERIX consortium, which can easily be adapted to other
high resolution instruments than SPIRou (e.g. VLT-CRIRES, MAROON-X, ELT-ANDES)
