EFFICIENT POOLING DESIGNS FOR LIBRARY SCREENING

We describe efficient methods for screening clone libraries, based on pooling schemes that we call ''random k-sets designs.'' In these designs, the pools in which any clone occurs are equally likely to be any possible selection of k from the v pools. The values of k and v can be chosen to optimize desirable properties. Random k-sets designs have substantial advantages over alternative pooling schemes: they are efficient, flexible, and easy to specify, require fewer pools, and have error-correcting and error-detecting capabilities. In addition, screening can often be achieved in only one pass, thus facilitating automation. For design comparison, we assume a binomial distribution for the number of ''positive'' clones, with parameters n, the number of clones, and c, the coverage. We propose the expected number of resolved positive clones-clones that are definitely positive based upon the pool assays-as a criterion for the efficiency of a pooling design. We determine the value of k that is optimal, with respect to this criterion, as a function of v, It, and c. We also describe superior h-sets designs called k-sets packing designs. As an illustration, we discuss a robotically implemented design for a 2.5-fold-coverage, human chromosome 16 YAC library of n = 1298 clones. We also estimate the probability that each clone is positive, given the pool-assay data and a model for experimental errors. (C) 1995 Academic Press, Inc.