Zimmerman, Kolea1; Levitis, Daniel2; Addicott, Ethan1; Pringle, Anne3

Published Aug 20, 2015 on Dryad. https://doi.org/10.5061/dryad.8br20

Abstract

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.

Mating Types of Strains

This file contains the mating type information for all the Neurospora crassa strains used to test the SPREAD algorithm. The column labelled "FGSC" lists the Fungal Genetics Stock Center strain IDs and the column labelled "mat" lists the mating type. "AA" = mating type "A", "a" = mating type "a".

strain_mating_type.csv

All pairwise matings with genetic and geographic distance data

This CSV contains all 576 possible pairwise matings between the 24 mat-a and 24 mat-A Neurospora crassa strains used to test the SPREAD algorithm. FGSC1 and FGSC2 are the strain IDs of the pair, GeneticDistance is the genetic distance between the pair (number of different SNPs between parents) and GeographicDistance is km between strain isolation locales.

all_matings_distance.csv

Simulated spore production data for all pairwise matings

This CSV contains the simulated spore production data used to compute the population GLMM. Subsets of this data-set were used to calculate sample GLMMs. Please see readme file for information on column names.

all_matings_spore_simulations.csv

Figure2 R Script

R script to produce figure 2 from data in the SPREAD_Rdata.zip file. To run script, working directory should be the directory containing the unzipped data files.

Figure2_SPREAD.R

Figure3 Table2 R script

R script to produce figure 3 and table 2 from data in the SPREAD_Rdata.zip file. To run script, working directory should be the directory containing the unzipped data files.

Figure3_Table2_SPREAD.R

Figure4 R Script

R script to produce figure 4 from data in the SPREAD_Rdata.zip file. To run script, working directory should be the directory containing the unzipped data files.

Figure4_SPREAD.R

Table1 R Script

R script to produce Table 2 from data in the SPREAD_Rdata.zip file. To run script, working directory should be the directory containing the unzipped data files.

Table1_SPREAD.R

SPREAD_Rdata

This zip file contains 6 rdata files and one CSV file used to produce the figures. Please refer to the ReadMe for descriptions.

Data from: Selection of Pairings Reaching Evenly Across the Data (SPREAD): a simple algorithm to design maximally informative fully crossed mating experiments

Data files

Abstract

Mating Types of Strains

All pairwise matings with genetic and geographic distance data

Simulated spore production data for all pairwise matings

Figure2 R Script

Figure3 Table2 R script

Figure4 R Script

Table1 R Script

SPREAD_Rdata

Data from: Selection of Pairings Reaching Evenly Across the Data (SPREAD): a simple algorithm to design maximally informative fully crossed mating experiments

Data files

Abstract

Usage notes

Mating Types of Strains

All pairwise matings with genetic and geographic distance data

Simulated spore production data for all pairwise matings

Figure2 R Script

Figure3 Table2 R script

Figure4 R Script

Table1 R Script

SPREAD_Rdata

Works referencing this dataset