DOI: 10.5061/dryad.h9w0vt4pj
title: Genotype likelihoods for low-coverage whole-genome sequencing data of yellow warblers

description: The following datasets include the required input files used to
 empirically test population assignment in WGSassign on Yellow Warbler
 data. The file "yewa.known.ind105.ds_2x.beagle.gz" includes the
 filtered variants of 105 Yellow Warbler individuals output as
 genotype likelihoods and stored in a Beagle-formatted file. The
 ID file, "yewa.known.ind105.reference.IDs.txt", is a
 tab-delimited file with 2 columns, the first being the sample ID, and the
 second being the known reference population. The sample order in the ID
 file should match that of the input beagle file. To measure the assignment
 accuracy of WGSassign, we used leave-one-out cross validation using the
 input beagle file and our ID file.
description: We used WGSassign on data from yellow warblers to test its
 accuracy when applied to individuals from a species exhibiting isolation
 by distance (Bay et al. 2021; Gibbs et al. 2000). Previous work on yellow
 warblers has found weak differentiation between populations, with pairwise
 FST values on the order of 0.01 or less (Gibbs et al. 2000). Blood samples
 from 105 individuals was collected via brachial venipuncture in the years
 2020 and 2021. These served as reference samples from 3 populations—North,
 Central, and South—previously described in Bay et al. (2021) and Gibbs et
 al. (2000). We extracted DNA from blood using the manufacturer’s protocol
 for Qiagen DNEasy Blood and Tissue Kits. Whole genome sequencing libraries
 were prepared following modifications of Illumina’s Nextera Library
 Preparation protocol (Schweizer & DeSaix 2023) and sequenced on a
 HiSeq 4000 at Novogene Corporation Inc., with a target sequencing depth of
 2X per individual. Sequences were trimmed with
 TrimGalore version 0.6.5 (https://github.com/FelixKrueger/TrimGalore) and mapped to the NCBI yellow warbler reference genome (Sayers et al. 2022) (accession number JANCRA010000000) using the Burrows-Wheeler Aligner software version 0.7.17 (Li & Durbin 2009). After mapping, the resulting SAM files were sorted, converted to BAM files, and indexed using Samtools version 1.9 (Li et al. 2009). We used MarkDuplicates from GATK version 4.1.4.0 (McKenna et al. 2010) to mark read duplicates and clipped overlapping reads with the clipOverlap function from bamUtil (https://genome.sph.umich.edu/wiki/BamUtil:_clipOverlap). To reduce sequencing depth variation, we used the DownsampleSam function from GATK to down-sample reads from BAM files with greater than 2X coverage, to 2X coverage. To identify genetic markers from low-coverage WGS data, we used stringent filtering options in ANGSD version 0.9.40 (Korneliussen et al. 2014). We retained reads with a mapping quality of at least 30 and base quality of at least 33. We retained SNPs that had read data in at least 50% of individuals and a minor allele frequency greater than 0.05. The filtered variants were output as genotype likelihoods and stored in a Beagle-formatted file.
description: # WGSassign Yellow Warbler Dataset --- The following datasets include the
 required input files used to empirically test population assignment in
 WGSassign on Yellow Warbler data. This includes a beagle file, entitled
 yewa.known.ind105.ds_2x.beagle.gz, and a text file entitled,
 yewa.known.ind105.reference.IDs.txt. ## Description of the data and file
 structure To measure the assignment accuracy of WGSassign, we used
 leave-one-out cross validation (the --loo specification in WGSassign)
 using the input beagle file (yewa.known.ind105.ds_2x.beagle.gz) and our ID
 file (yewa.known.ind105.reference.IDs.txt). The file
 "yewa.known.ind105.ds_2x.beagle.gz" includes the filtered
 variants of 105 Yellow Warbler individuals output as genotype likelihoods
 and stored in a Beagle-formatted file. In a Beagle-formatted file, the
 first column is the marker chromosome and position, the second column is
 the major allele, and the third column is the minor allele. The following
 columns include three columns per individual, where the first column is
 the genotype likelihood for the major/major genotype for the individual,
 the fifth column is the genotype likelihood for the major/minor genotype
 for the individual, and the sixth column is the genotype likelihood for
 the minor/minor genotype for the first individual. The ID file is a
 tab-delimited file with 2 columns, the first being the sample ID, and the
 second being the known reference population where the sample was collected
 from. The sample order in the ID file should match the sample order for
 the columns in the input beagle file. Leave-one-out cross validation was
 run using the script
 [WGSassign.loo.sh](https://github.com/mgdesaix/WGSassign-manuscript-data/blob/main/yellow-warbler/WGSassign.loo.sh). ## Sharing/Access information The script used to run Leave-one-out cross validation in WGSassign as well as the R-script used to check assignment accuracy was run using the scripts found at .