Stochastic threshold group testing

Abstract

We formulate and analyze a stochastic threshold group testing problem motivated by biological applications. Here a set of n items contains a subset of d ≪ C n defective items. Subsets (pools) of the n items are tested. The test outcomes are negative if the number of defectives in a pool is no larger than l; positive if the pool contains more than u defectives, and stochastic (negative/positive with some probability) if the number of defectives in the pool is in the interval [l, u]. The goal of our stochastic threshold group testing scheme is to identify the set of d defective items via a “small” number of such tests with high probability. In the regime that l = o(d) we present schemes that are computationally feasible to design and implement, and require near-optimal number of tests. Our schemes are robust to a variety of models for probabilistic threshold group testing.