Assessing kinship detection: Single nucleotide polymorphism array density and estimator comparison in white-tailed deer

Single nucleotide polymorphism (SNP) arrays have become increasingly popular due to their affordability, commercial availability, statistical power, and reproducibility. These arrays are being developed commercially for a wide range of species in various density formats. In this study, we evaluated the ability of commercially available medium-density (72,732 SNPs) and high-density SNP (702,183 SNPs) array for white-tailed deer (Odocoileus virginianus) to accurately identify known genetically related individuals within a wild population. We also assessed the impact of SNP filtering thresholds on relatedness analyses and compared the performance of four common relatedness softwares: KING, COLONY, Sequoia, and COANCESTRY, on these known related pairs. Our analysis revealed that the medium-density array exhibited greater tolerance to filtering and lower sensitivity to bioinformatic pipelines, making it a favorable balance between cost, computational time, and statistical power for analyses ..., , # Assessing kinship detection: Single nucleotide polymorphism array density and estimator comparison in white-tailed deer

Dataset DOI: [10.5061/dryad.m63xsj4fm](https://doi.org/10.5061/dryad.m63xsj4fm)

## Description of the data and file structure

Kinship_Detection.zip: Genotyping data from white-tailed deer samples generated using the Axiom OVSNP600 and Axiom OVSNP60 genotyping arrays (Thermo Fisher Scientific). Genotype data are provided in Variant Call Format (VCF) files. Input files for the software programs COLONY (Jones and Wang 2010), COANCESTRY (Wang 2011), and Sequoia (Huisman 2017), all prepared using R, are included. Additionally, metadata are available for all individuals, including information on known genetically related pairs.

We have submitted our raw data (raw unfiltered genomic data in the folder “VCF”, known related individual information (Known_Genetic_Relationships), metadata for all the individuals in our analysis (MNDNR_SamplesForSNPsProjec_Modified4publicrele...,