Molecular analysis has become one of the major tools used for viral outbreak investigation and transmission network inference. We present two novel methods for accurate identification of transmission clusters and sources of infection for highly heterogeneous viruses such as HIV and HCV. Validation on data obtained from HCV outbreaks shows that the proposed algorithms outperform the state-of-the-art consensus-based methods both in true and false positive rates for transmission prediction, as well as in accuracy of source identification for outbreaks.