In audio source separation, reference guided approaches are a class of methods that use reference signals to guide the separation. In prior work, we proposed a general framework to model the deformation between the sources and the references. In this paper, we investigate a specific scenario within this framework: music separation guided by the multitrack recording of a cover interpretation of the song to be processed. We report a series of experiments highlighting the relevance of joint Non-negative Matrix Factorization (NMF), dictionary transformation, and specific transformation models for different types of sources. A signal-to-distortion ratio improvement (SDRI) of almost 11 decibels (dB) is achieved, improving by 2 dB compared to previous study on the same data set. These observations contribute to validate the relevance of the theoretical general framework and can be useful in practice for designing models for other reference guided source separation problems.