Data from: Genotyping-by-sequencing for estimating relatedness in non-model organisms: avoiding the trap of precise bias ...

• Main Authors: Attard, Catherine R.M., Beheregaray, Luciano B., Moller, Luciana M., Attard, Catherine R. M.
• Format: Dataset
• Language: English
• Published: Dryad 2017
• Subjects: pedigree; low coverage; relationships; Next-generation sequencing; Balaenoptera musculus; Holocene; double-digest restriction-site associated DNA ddRAD
• Online Access: https://dx.doi.org/10.5061/dryad.t8ph5; https://datadryad.org/stash/dataset/doi:10.5061/dryad.t8ph5

There has been remarkably little attention to using the high resolution provided by genotyping-by-sequencing (i.e. RADseq and similar methods) datasets for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of dataset that could lead to downward-biased, yet precise, estimates of relatedness. Here we assess the applicability of genotyping-by-sequencing datasets for relatedness inferences given their relatively high genotyping error rates. Individuals of known relatedness were simulated under genotyping error, allelic dropout, and missing data scenarios based on an empirical ddRAD dataset, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (1996) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We ... : SNP genotypesGenotype data in COANCESTRY format for 8,294 SNPsCOANCESTRY_input.txtMicrosatellite genotypeGenotype data for one individual at 20 microsatellites. The microsatellite genotypes for the remaining individuals are available in a previous Dryad entry, doi:10.5061/dryad.8m0t6 . The format of the data in the current Dryad entry is the same as the previous entry, except in the current entry there is no sex data column.Microsatellite_genotype.txt ...