ComplexSelection

This repository houses code and data to identify selection on traits controlled by many loci. The corresponding paper, "a simple test identifies selection on complex traits", is available at Genetics. In this repository, we have divided files into subdirectories as outlined below. For analyses performed using R-markdown, we have deposited both raw files and html outputs.

Function: R function to estimate G-hat from allele frequency and effect size data.

• Ghat.R: R function to estimate G-hat from allele frequency and effect size data.

Maize: Code to analyze maize data

• Frequency_change_rrBlup_reverseInlay.Rmd: Code to calculate allele frequencies, estimate effects, and run analysis on maize data.

• Frequency_change_rrBlup_reverseInlay.html: HTML-readable code.

• ld_calc_maize_03.r: Code to calculate LD decay in maize data.

Chickens: Code to analyze chicken data

• Frequency_change_rrBlup_reverse_inset_EW1.Rmd: Code to calculate allele frequencies, estimate effects, and run analysis on chicken data.

• Frequency_change_rrBlup_reverse_inset_EW1.html: HTML-readable code.

• Frequency_change_rrBlup_outliers_removed_EW1.Rmd: Code to calculate allele frequencies, estimate effects, and run analysis on chicken data, with outliers removed.

• Frequency_change_rrBlup_outliers_removed_EW1.html: HTML-readable code.

• ld_calc_chicken.r: Code to calculate LD decay in chicken data.

Simulations: Code to run and analyze simulation code

• qtl_10.prm: 10-QTL simulation parameter file

• run_10.sh: 10-QTL simulation submission script for OpenLava cluster

• Analyze10.Rmd: Code to analyze 10-QTL simulation

• Analyze10.html: HTML-readable code

• Map10.Rmd: Code to do seleciton mapping in 10-QTL simulation

• Map10.html: HTML-readable code

• Analyze10_L44.Rmd: Code to tune LD threshold for determining M_eff. Code determines mean LD decay over a specific distance (Specified in the 44th line of the QMSim LD output file for the 10-QTL simulation)and calculate the false positive rate. This example script was repeatedly run for lines 44-58 and used to create raw data for generating the M_eff supplemental figure in the manuscript.

• qtl_50.prm: 50-QTL simulation parameter file

• run_50.sh: 50-QTL simulation submission script for OpenLava cluster

• Analyze50.Rmd: Code to analyze 50-QTL simulation

• Analyze50.html: HTML-readable code

• Map50.Rmd: Code to do seleciton mapping in 50-QTL simulation

• Map50.html: HTML-readable code

• Analyze50_L44.Rmd: Code to tune LD threshold for determining M_eff. Code determines mean LD decay over a specific distance (Specified in the 44th line of the QMSim LD output file for the 50-QTL simulation)and calculate the false positive rate. This example script was repeatedly run for lines 44-58 and used to create raw data for generating the M_eff supplemental figure in the manuscript.

• qtl_100.prm: 100-QTL simulation parameter file

• run_100.sh: 100-QTL simulation submission script for OpenLava cluster

• Analyze100.Rmd: Code to analyze 100-QTL simulation

• Analyze100.html: HTML-readable code

• Map100.Rmd: Code to do selection mapping in 100-QTL simulation

• Map100.html: HTML-readable code

• Analyze100_L44.Rmd: Code to tune LD threshold for determining M_eff. Code determines mean LD decay over a specific distance (Specified in the 44th line of the QMSim LD output file for the 100-QTL simulation)and calculate the false positive rate. This example script was repeatedly run for lines 44-58 and used to create raw data for generating the M_eff supplemental figure in the manuscript.

• qtl_1000.prm: 1000-QTL simulation parameter file

• run_1000.sh: 1000-QTL simulation submission script for OpenLava cluster

• Analyze1000.Rmd: Code to analyze 1000-QTL simulation

• Analyze1000.html: HTML-readable code

• Map1000.Rmd: Code to do seleciton mapping in 1000-QTL simulation

• Map1000.html: HTML-readable code

• Analyze1000_L44.Rmd: Code to tune LD threshold for determining M_eff. Code determines mean LD decay over a specific distance (Specified in the 44th line of the QMSim LD output file for the 1000-QTL simulation)and calculate the false positive rate. This example script was repeatedly run for lines 44-58 and used to create raw data for generating the M_eff supplemental figure in the manuscript.

• qtl_10000.prm: 10000-QTL simulation parameter file

• run_10000.sh: 10000-QTL simulation submission script for OpenLava cluster

• Analyze10000.Rmd: Code to analyze 10000-QTL simulation

• Analyze10000.html: HTML-readable code

• Map10000.Rmd: Code to do seleciton mapping in 10000-QTL simulation

• Map10000.html: HTML-readable code

• LD_Thresh_Fig.R: R code to compile LD threshold information for generating M_eff supplemental figure and determining appropriate M_eff.

• PowerFigure.R: Code to compile power information comparing G-hat to Fst mapping and generate Figure 1 in the manuscript.

• intermittent.prm Intermittent selection parameter file.

• on20off5.Rmd Code to analyze simulation involving 20 gens with selection followed by 5 without.

• on20off5.html HTML-readable code

• on20off20.Rmd Code to analyze simulation involving 20 gens with selection followed by 20 without.

• on20off20.html HTML-readable code

• on20off50.Rmd Code to analyze simulation involving 20 gens with selection followed by 50 without.

• on20off50.html HTML-readable code

• on20off100.Rmd Code to analyze simulation involving 20 gens with selection followed by 100 without.

• on20off100.html HTML-readable code

• on1off5.Rmd Code to analyze simulation involving 1 gens with selection followed by 5 without.

• on1off5.html HTML-readable code

• on1off20.Rmd Code to analyze simulation involving 1 gens with selection followed by 20 without.

• on1off20.html HTML-readable code

• intensity.prm Parameter file for variable selection intensity.

• intensity01.Rmd Code to analyze simulation involving a selected proportion of 1 percent.

• intensity01.html HTML-readable code

• intensity05.Rmd Code to analyze simulation involving a selected proportion of 5 percent.

• intensity05.html HTML-readable code

• intensity5.Rmd Code to analyze simulation involving a selected proportion of 50 percent.

• intensity5.html HTML-readable code

• sampleSize.RData Code to analyze effect of sample size.

• sampleSize.html HTML-readable code.

• gens.prm Parameter file for variable numbers of generations

• Gens1.Rmd Code to analyze 1 generation of selection

• Gens1.html HTML-readable code

• Gens10.Rmd Code to analyze 10 generation of selection

• Gens10.html HTML-readable code

• Gens50.Rmd Code to analyze 50 generation of selection

• Gens50.html HTML-readable code

• Gens100.Rmd Code to analyze 100 generation of selection

• Gens100.html HTML-readable code

• phenotypeGen.prm Parameter file for varying phenotyping generation.

• Phen0.Rmd Code to analyze phenotyping in generation 0

• Phen0.html HTML-readable code

• Phen10.Rmd Code to analyze phenotyping in generation 10

• Phen10.html HTML-readable code

Data

• Maize data are published in:

  • Lorenz, A. J., Beissinger, T.M., Rodrigues, R., de Leon, N. 2015. Selection for silage yield and composition did not affect genomic diversity within the Wisconsin Quality Synthetic maize population. Genes Genomes Genetics. DOI: 10.1534/g3.114.015263.

• Chicken data are available from Figshare.