We have developed a semi-automated data quality assessment and monitoring workflow based on nucleic acid multi-omics reference materials. This system is designed to address challenges such as inconsistent data quality, significant batch effects, and discordant variant detection encountered during the production, analysis, and integration of nucleic acid high-throughput sequencing data—particularly in multi-omics contexts including genomics and transcriptomics—by providing standardized evaluation metrics. Through standardized, quantitative, and comprehensive measurement and visualization of data quality throughout the entire workflow, it ensures the reliability, reproducibility, and comparability of downstream analyses (such as variant calling and gene expression quantification), thereby establishing a high-quality data cornerstone for precision medicine research.