Hi, I am working with a bunch of microbiologists which with I conduct metagenomic analyses. In the past (not so old), I did my PhD thesis on Bayesian Network classification (a supervised classification approach), then, turning to more sensu stricto bioinformatic tasks started on my first postdoc, my PhD experience made me more sensitive to classification approaches whenever it's possible, for instance, when I want to screen (in silico) my metagenome sequences.
So, when coworkers ask me for a RNA16S (rrs gene) analysis, I propose a RDP classifier approach (based on a Naive Bayes method), or a HHMER approach for a functional screening. But most of the time, they don't like, they do prefer BLAST. It's slower, but, according to them the results are more accurate, and most importantly, more relevant according to their expectations. I try to explain what the differences between the 2 approaches (essentially classifiers are based on learnt profiles which is supposed to be more relevant when the goal is to classify), but obviously without success.
Regarding to my lack of arguments, and before investigating deeper this "issue" by myself, I would like to have your opinion about that. Thanks a lot.