%0 Journal Article
%A Zimmerman, Kolea
%A Levitis, Daniel
%A Addicott, Ethan
%A Pringle, Anne
%T Selection of Pairings Reaching Evenly Across the Data (SPREAD): A simple algorithm to design maximally informative fully crossed mating experiments
%D 2015
%R 10.1101/009720
%J bioRxiv
%P 009720
%X We present a novel algorithm for the design of crossing experiments. The algorithm identifies a set of individuals (a “crossing-set”) from a larger pool of potential crossing-sets by maximizing the diversity of traits of interest, for example, maximizing the range of genetic and geographic distances between individuals included in the crossing-set. To calculate diversity, we use the mean nearest neighbor distance of crosses plotted in trait space. We implement our algorithm on a real dataset of Neurospora crassa strains, using the genetic and geographic distances between potential crosses as a two-dimensional trait space. In simulated mating experiments, crossing-sets selected by our algorithm provide better estimates of underlying parameter values than randomly chosen crossing-sets.
%U https://www.biorxiv.org/content/biorxiv/early/2015/06/25/009720.full.pdf