DOI: 10.5061/dryad.3mq4631
title: Data from: Attack of the PCR clones: rates of clonality have little effect on RAD-seq genotype calls

description: Interpretation of high-throughput sequence data requires an understanding
 of how decisions made during bioinformatic data processing can influence
 results. One source of bias that is often cited is PCR clones (or PCR
 duplicates). PCR clones are common in restriction site associated
 sequencing (RAD-seq) datasets, which are increasingly being used for
 molecular ecology. To determine the influence PCR clones and the
 bioinformatic handling of clones have on genotyping, we evaluate four
 RAD-seq datasets. Datasets were compared before and after clones were
 removed to estimate the number of clones present in RAD-seq data, quantify
 how often the presence of clones in a dataset cause genotype calls to
 change compared to when clones were removed, investigate the mechanisms
 that lead to genotype call changes, and test if clones bias heterozygosity
 estimates. Our RAD-seq datasets contained 30 – 60% PCR clones, but 95% of
 RAD-tags had five or fewer clones. Relatively few genotypes changed once
 clones were removed (5-10%), and the vast majority of these changes (98%)
 were associated with genotypes switching from a called to no-call state or
 vice versa. PCR clones had a larger influence on genotype calls in
 individuals with low read depth but appeared to influence genotype calls
 at all loci similarly. Removal of PCR clones reduced the number of called
 genotypes by 2% but had almost no influence on estimates of
 heterozygosity. As such, while steps should be taken to limit PCR clones
 during library preparation, PCR clones are likely not a substantial source
 of bias for most RAD-seq studies.
description: Brook trout clone
 filteredClone filtered VCF file
 of brook trout genotype data. VCF files were generated using stacks 2.46
 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data was
 generated using the SbfI enzyme, methods outlined in Ali et al. (2016)and
 prepared in the Genomic Variation Lab at the University of
 California--Davis and sequenced on Illumina NextSeq 500 (PE 75 bp reads,
 96 samples/lane) at the Cornell Institute of
 Biotechnology.bt_CF.vcfBrook trout unfilteredNon-clone filtered (unfiltered) VCF file of brook trout genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data was generated using the SbfI enzyme, methods outlined in Ali et al. (2016)and prepared in the Genomic Variation Lab at the University of California--Davis and sequenced on Illumina NextSeq 500 (PE 75 bp reads, 96 samples/lane) at the Cornell Institute of Biotechnologybt_noCF.vcfCisco clone filteredClone filtered (filtered) VCF file of cisco genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 96 samples/lane) at the Michigan State Genomics Core Facility.cisco_CF.vcfCisco unfilteredNon-clone filtered (unfiltered) VCF file of cisco genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 96 samples/lane) at the Michigan State Genomics Core Facility.cisco_noCF.vcfWalleye clone filteredClone filtered (filtered) VCF file of walleye genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 192 samples/lane) at the Michigan State Genomics Core Facility.wal_CF.vcfWalleye unfilteredNon-clone filtered (unfiltered) VCF file of walleye genotype data. Clone filtered (filtered) VCF file of walleye genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 192 samples/lane) at the Michigan State Genomics Core Facility.wal_noCF.vcf