Deep sequencing is able to generate a complete picture of the retroviral quasi-species in a patient. We demonstrate that the unprecedented power of deep sequencing in conjunction with computational data analysis has great potential for clinical diagnostics and basic research. Specifically, we analyzed longitudinal deep sequencing data from patients in a study with Vicriviroc, a drug that blocks the HIV-1 co-receptor CCR5. Sequences covered the V3-loop of gp120, known to be the main determinant of co-receptor tropism. First, we evaluated this data with a computational model for the interpretation of V3-sequences with respect to tropism, and we found complete agreement with results from phenotypic assays. Thus, the method could be applied in cases where phenotypic assays fail. Second, computational analysis led to the discovery of a characteristic pattern in the quasi-species that foreshadows switches of co-receptor tropism. This analysis could help to unravel the mechanism of tropism switches, and to predict these switches weeks to months before they can be detected by a phenotypic assay.