Data and scripts for "Defining conservation units in a highly diverse species: A case on Arctic charr" by Sam Fenton, Colin W. Bean, Samuel A.M. Martin, Samuel J. Poultney, Anthony Smith, Elvira de Eyto, Kathryn R. Elmer & Colin E. Adams


-Sample_list provides a list of all individuals across the dataset and the Accession numbers for raw data on NCBI.

-Filtered.snps.vcf is the VCF file for the filtered SNP data (N=24,878 SNPs and 410 individuals). The same data is also provided in GenePop (.gen) and plink raw (.raw) format. The map file is used in conjunction with .raw file.

- The neutral_snps_PopCluster files (.dat and .PcPjt) contain the input genetic data (N= 22763 SNPs and 410 individuals) and the settings used to run the admixture analysis in PopCluster 

-Strata_List provides a list of the hydrometric area of origin for each lake and which side of the east-west split in the Neighbour-joining tree providing the information needed for the AMOVA analysis 

-Bathymetric_environmental_data provides a list of the all the climatic and lake variable data used to identify putatively adaptive SNPs

-Data_for_Gradient_Forest contains the data used for the Genetic offset analysis. This includes the variable data for the 6 uncorrelated climatic variables used and minor allele frequencies for the adaptive SNPs used (N=235)

-Lake_latitude_longitude contains the latitude and longitude co-ordinates used for each lake of origin to get relevant current and future climatic data from WorldClim

-The Lake_environmental_data and Lake_environmental_data_future_RCP_45 contain the climatic data from the 19 variables collected from WorldClim for current and future scenarios respectively 

- Two R files are provided for the analyses run. Genetic_analyses contains the scripts used to run the neighbour-joining tree, AMOVA, and estimate allelic richness. Adaptive_SNPs_Genetic_Offset contains the code to identify the putatively adaptive SNPs via RDA and then run the genetic offset analysis using gradientForest

