Read Me

# C. Vlachos, C. Burny, M. Pelizzola, R. Borges
# May 2019

# Licence
# All scripts are distributed under the GPL-3.0 (GNU General Public License, version 3)

# ----- Description of the scripts ----- #

#run_ROC.sh: bash script to compute predictions files and create ROC curves
#rocr-generate-predictionlist.py: create predictions files across 100 simulations per scenario for ranking 
#roc-curve.R: plot ROC curve and compute AUC (uncomment the corresponding lines)

#estimate_Ne_per_simulation_run.R: estimate Ne for one simulation run for each of the 10 replicates 
#Save_frequency_from_sync.R: convert sync file into frequency matrix 

#fit.sh: bash script to run FIT tests using parallel and merge outputs 
#fit12.R: R script to do the t-tests defining in Feder 2014 paper, adapted from A. Feder
#input_roc_FIT12.r: transform output from fit.sh to input for building ROC curves
#merge_rds_FIT.R: script to merge outputs from parallelization 
#prepare_input_files_FIT.R: prepare input file to run FIT1 and FIT2 tests 

#input_roc_slattice.r: transform output from slattice.R to input for building ROC curves
#prepare_input_files_slattice.r: prepare input file to slattice
#slattice.R: script to run slattice (simplified from run on Hadoop cluster) 

#LRT.benchmarking.py: python script adapted from J.K. Kelly that run LRT-1 and LRT-2 tests 
#bash_run_LRT12.sh: bash script to run LRT-1 and LRT-2 tests on prepared input data
#input_roc_LRT12.R: transform output from bash_run_LRT12.sh to input for building ROC curves 
#prepare_input_files_LRT12.R: prepare input file to run LRT-1 and LRT-2 tests
#CHISQ.R: R script to run the chi-square test from PoolSeq (Taus et al. 2017)
#E-R_CHISQ.R: R script to run the e&r chi-square test from ACER (Spitzer et al. 2019)
#E-R_CMH.R: R script to run the e&r cmh test from ACER (Spitzer et al. 2019)
#LLS_LinuxCluster.R: R script (with bash command calling this script as header) to run LLS test from PoolSeq (Taus et al. 2017)  


#make_boxplot_heterogenity.R: create Supplem. Fig. 8 to extract shared allele frequency changes and replicate specific changes from .LRT.txt output, compute CV and make boxplots