GigaScienceBioinformaticsPeer-reviewed journal article
Comparative analysis of seven short-reads sequencing platforms using the Korean Reference Genome: MGI and Illumina sequencing benchmark for whole-genome sequencing
Hak‐Min KimiD, Sungwon JeoniD, Oksung Chung, Je Hoon JuniD, Hui-Su KimiD, Asta BlažytėiD, Hwang-Yeol Lee, Youngseok Yu, Yun Sung ChoiD, Dan M BolseriD, Jong BhakiD
Abstract
BackgroundMGISEQ-T7 is a new whole-genome sequencer developed by Complete Genomics and MGI utilizing DNA nanoball and combinatorial probe anchor synthesis technologies for generating short reads at a very large scale - up to 60 human genomes per day. However, it has not been objectively and systematically compared against Illumina short-read sequencers. FindingsBy using the same KOREF sample, the Korean Reference Genome, we have compared seven sequencing platforms including BGISEQ-500, MGISEQ-T7, HiSeq2000, HiSeq2500, HiSeq4000, HiSeqX10, and NovaSeq6000. We measured sequencing quality by comparing sequencing statistics (base quality, duplication rate, and random error rate), mapping statistics (mapping rate, depth distribution, and %GC coverage), and variant statistics (transition/transversion ratio, dbSNP annotation rate, and concordance rate with SNP genotyping chip) across the seven sequencing platforms. We found that MGI platforms showed a higher concordance rate of SNP genotyping than HiSeq2000 and HiSeq4000. The similarity matrix of variant calls confirmed that the two MGI platforms have the most similar characteristics to the HiSeq2500 platform. ConclusionsOverall, MGI and Illumina sequencing platforms showed comparable levels of sequencing quality, uniformity of coverage, %GC coverage, and variant accuracy, thus we conclude that the MGI platforms can be used for a wide range of genomics research fields at approximately half the cost of the Illumina platforms.
- assay: whole-genome sequencing
- research focus: benchmarking
- research focus: variant calling
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 79
- FWCI
- 3.21
- Field percentile
- top 6%
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