Benchmarking sequence performance of different MGI Library Prep Sets on the DNBSEQ-T7 using Genome in a Bottle reference genomes
Here we present a WGS dataset of the GIAB Ashkenazi Jewish trio generated on the DNBSEQ-T7 platform using the three library strategies together with variant benchmarking against GIAB truth sets. The dataset was generated to evaluate DNBSEQ-T7 performance across library preparation methods (MGIEasy Universal, PCR-FREE and Fast FS) in a South African setting, considering workflow efficiency, cost, and performance. It may be reused to support the local genomics community in selecting the most appropriate WGS strategy for their specific sample context, particularly where sample quality or input constraints may influence the optimal choice of library preparation method, as well as for benchmarking variant calling pipelines and assessing platform reproducibility.
Here we present a WGS dataset of the GIAB Ashkenazi Jewish trio generated on the DNBSEQ-T7 platform using the three library strategies together with variant benchmarking against GIAB truth sets. The dataset was generated to evaluate DNBSEQ-T7 performance across library preparation methods (MGIEasy Universal, PCR-FREE and Fast FS) in a South African setting, considering workflow efficiency, cost, and performance. It may be reused to support the local genomics community in selecting the most appropriate WGS strategy for their specific sample context, particularly where sample quality or input constraints may influence the optimal choice of library preparation method, as well as for benchmarking variant calling pipelines and assessing platform reproducibility.
South African Medical Research Council