Group testing DNA Microarrays for detection of biological agents

Invited Talk presented on May 19, 2006 by Alexander Schliep at DIMACS workshop on combinatorial group testing.

Abstract: The reliable identification of presence or absence of biological agents (targets), such as viruses or bacteria, is crucial for many applications from health care to biodiversity. If genomic sequences of targets are known, hybridization reactions between oligonucleotide probes and targets performed on suitable DNA microarrays will allow to infer presence or absence from the observed pattern of hybridization. Targets, for example all known strains of HIV, are often closely related and finding unique probes becomes impossible. We employ a group testing approach, where groups of targets are defined by the same, non-unique, oligonucleotide probe binding to them. In combination with decoding techniques from statistical group testing, this allows to detect known targets with great success. Note, that here the group testing design cannot be chosen arbitrarily. It is selected from all the sets defined by the non-unique probes. Of great relevance, however, is the problem of identifying the presence of previously unknown targets or of targets that evolve rapidly. We present the first approach to decode hybridization experiments using non-unique probes when targets are related by a phylogenetic tree. By use of a Bayesian framework and a Markov chain Monte Carlo approach we are able to identify over 95% of known targets and assign up to 70% of unknown targets to their correct clade in hybridization simulations on biological and simulated data.