Slow speed of the Next-Generation sequencing data analysis, compared to the latest high throughput sequencers such as HiSeq X system, using the current industry standard genome analysis pipeline, has been the major factor of data backlog which limits the real-time use of genomic data for precision medicine. This study demonstrates the DRAGEN Bio-IT Processor as a potential candidate to remove the "Big Data Bottleneck". DRAGEN TM accomplished the variant calling, for ~40× coverage WGS data in as low as ~30 minutes using a single command, achieving the over 50-fold data analysis speed while maintaining the similar or better variant calling accuracy than the standard GATK Best Practices workflow. This systematic comparison provides the faster and efficient NGS data analysis alternative to NGS-based healthcare industries and research institutes to meet the requirement for precision medicine based healthcare.

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Objective: To improve the detecting accuracy of chromosomal aneuploidy of fetus by non-invasive prenatal testing (NIPT) using next generation sequencing data of pregnant women's cell-free DNA. Methods: We proposed the multi-Z method which uses 21 z-scores for each autosomal chromosome to detect aneuploidy of the chromosome, while the conventional NIPT method uses only one z-score. To do this, mapped read numbers of a certain chromosome were normalized by those of the other 21 chromosomes. Average and standard deviation (SD), which are used for calculating z-score of each sample, were obtained with normalized values between all autosomal chromosomes of control samples. In this way, multiple z-scores can be calculated for 21 autosomal chromosomes except oneself. Results: Multi-Z method showed 100% sensitivity and specificity for 187 samples sequenced to 3 M reads while the conventional NIPT method showed 95.1% specificity. Similarly, for 216 samples sequenced to 1 M reads, Multi-Z method showed 100% sensitivity and 95.6% specificity and the conventional NIPT method showed a result of 75.1% specificity. Conclusion: Multi-Z method showed higher accuracy and robust results than the conventional method even at low coverage reads.

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