  Spectroscopy of exoplanetary atmospheres has become a well established method
for the characterisation of extrasolar planets. We here present a novel inverse
retrieval code for exoplanetary atmospheres. TauRex (Tau Retrieval for
Exoplanets) is a line-by-line radiative transfer fully Bayesian retrieval
framework. TauRex includes the following features: 1) the optimised use of
molecular line-lists from the Exomol project; 2) an unbiased atmospheric
composition prior selection, through custom built pattern recognition software;
3) the use of two independent algorithms to fully sample the Bayesian
likelihood space: nested sampling as well as a more classical Markov Chain
Monte Carlo approach; 4) iterative Bayesian parameter and model selection using
the full Bayesian Evidence as well as the Savage-Dickey Ratio for nested
models, and 5) the ability to fully map very large parameter spaces through
optimal code parallelisation and scalability to cluster computing. In this
publication we outline the TauRex framework and demonstrate, using a
theoretical hot-Jupiter transmission spectrum, the parameter retrieval and
model selection. We investigate the impact of Signal-to-Noise and spectral
resolution on the retrievability of individual model parameters, both in terms
of error bars on the temperature and molecular mixing ratios as well as its
effect on the model's global Bayesian evidence.
