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Background. Several studies have used phylogenetics to investigate HumanImmunodeficiency Virus (HIV) transmission among Men who have Sex with Men(MSMs) in Montreal, Quebec, Canada, revealing many transmission clusters. TheQuebec HIV genotyping program sequence database now includes viral sequencesfrom close to 4,000 HIV-positive individuals classified as MSMs. In this paper,we investigate clustering in those data by comparing results from severalmethods: the conventional Bayesian and maximum likelihood-bootstrap methods,and two more recent algorithms, DM-PhyClus, a Bayesian algorithm that producesa measure of uncertainty for proposed partitions, and the Gap Procedure, a fastdistance-based approach. We estimate cluster growth by focusing on recent casesin the Primary HIV Infection (PHI) stage. Results. The analyses revealconsiderable overlap between cluster estimates obtained from conventionalmethods. The Gap Procedure and DM-PhyClus rely on different cluster definitionsand as a result, suggest moderately different partitions. All estimates lead tosimilar conclusions about cluster expansion: several large clusters haveexperienced sizeable growth, and a few new transmission clusters are likelyemerging. Conclusions. The lack of a gold standard measure for clusteringquality makes picking a best estimate among those proposed difficult. Workaiming to refine clustering criteria would be required to improve estimates.Nevertheless, the results unanimously stress the role that clusters play inpromoting HIV incidence among MSMs.

Transmission clusters in the HIV-1 epidemic among men who have sex with men in Montreal, Quebec, Canada