RT Journal Article
SR Electronic
T1 Selection of Pairings Reaching Evenly Across the Data (SPREAD): A simple algorithm to design maximally informative fully crossed mating experiments
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 009720
DO 10.1101/009720
A1 Kolea Zimmerman
A1 Daniel Levitis
A1 Ethan Addicott
A1 Anne Pringle
YR 2015
UL http://biorxiv.org/content/early/2015/02/05/009720.abstract
AB 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.