T/LTIA 13-2021 Gene testing service standard for sharing microbiome data

Scope

Scope: This document specifies the norms for data sharing and exchange of microbiome data among data processing nodes in genetic testing services, as well as the metadata and data exchange formats. This document applies to microbiome data in genetic testing services. Main technical content: During the development of this standard, with the deepening of research, the standard discussion draft, draft, and solicitation for comments were successively completed, and the standard content was continuously improved and became more scientific and reasonable. According to the needs, the main technical content of this standard is determined as follows: In terms of terms and definitions, the metadata, microbiome, metagenomics, amplicons, biological observation matrix format, data production, data analysis, analysis-level data, data storage, data services, gene abundance, taxonomic abundance, functional abundance, relative abundance, operational taxonomic units, FASTQ format, TSV format, etc. are defined. In the process of microbiome data sharing and exchange, the production, transmission, and use of microbiome data are described. This process is divided into four links: data production, data analysis, data storage, and data services, and the details and key points of each link are described. In the microbiome data metadata, the standard divides the metadata into three parts according to the link of data generation: sample information-related metadata, sequencing data-related metadata, and analysis-level data-related metadata, and standardizes the commonly used metadata and minimum elements in the exchange of microbiome data in each part. In the microbiome data format, the standard standardizes the data format of microbiome data in various process links and introduces commonly used formats for reference. According to the link of generation, microbiome data is divided into raw data and analysis-level data. The raw data of high-throughput sequencing methods is FASTQ, and the analy

Development Information

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