THE LIMITS OF RANDOM FINGERPRINTING

Various random fingerprinting methods are sometimes used to detect ove rlap between pairs of clones as a first step toward producing a minima l tiling path of clones for subsequent mapping and sequencing efforts. This paper evaluates and compares various statistical procedures for detecting pairwise overlap between clones when the fingerprints arise from any random process meeting simple, plausible assumptions about th e relationship between overlap and the resulting fingerprint. Examples of such random processes include, but are not limited to, large-scale hybridization procedures designed to prepare thing paths of clones fo r subsequent large-scale genomic sequencing. Our goals are to assess h ow well random fingerprinting can possibly detect overlap, to assess t he effects of inevitable fingerprinting errors on statistical detectio n, to determine how one can make the best use of the data random finge rprinting provides, and to evaluate how well simple, heuristic techniq ues for overlap detection compare to more complex, likelihood-based ap proaches. The paper provides a quantitative assessment of the ability of any random fingerprinting procedure to detect various proportions o f clonal overlap and shows the extent to which a small amount of exper imental error will vitiate the performance of such techniques. The pap er outlines a simple approximation method for constructing Bayesian ov erlap detectors, while concluding that detectors constructed from line ar combinations of fingerprint data can be designed that will perform nearly as well as more complex, likelihood-based approaches. (C) 1997 Academic Press.