Variant calls derived from different sources can be combined once correct quality procedures are followed and ensure that all genotypes are called based on the reference and alternate allele. It’s essential to follow a rigorous workflow to maintain data quality and consistency.

Verify that all datasets are aligned to the same reference genome version

Use tools like bcftools to ensure consistent formatting across VCF files

Filter variants based on standard Quality Metrics and extract biallelic SNPs

Identify and Extract Common Variants

Merge data sets by variant position

Post-Merging QC - Principal Component Analysis and relatedness checks

Additional QC Steps - Hardy-Weinberg Equilibrium and minor allele frequency

After these steps, your dataset will be ready for downstream analyses.

Behnam Derakhshani , Yes, it’s possible to combine GBS and WGS data for variant calling and GWAS, but it requires a harmonized workflow.

Although GBS (reduced representation) and WGS (whole-genome coverage) differ in scope, you can align both datasets to the same reference genome and perform joint variant calling (e.g., using GATK’s GVCF-based pipeline). After calling, it's important to retain only the variant sites covered by GBS across your population, to ensure comparability.

The WGS data from the two parents can be especially helpful for variant discovery and imputation —just make sure to account for the differences in coverage and sequencing depth during filtering and downstream analysis.

This approach is fairly common in crop GWAS studies, but watch out for high missingness in GBS data, and consider imputation before association testing.