PD ISO/TS 22690:2021

What is ISO/TS 22690 about? 

ISO/TS 22690 specifies reliability assessment criteria for high-throughput gene-expression data. It is applicable to assessing the accuracy, reproducibility, and comparability of gene-expression data that are generated from microarray, next-generation sequencing, and other forms of high-throughput technologies. 

ISO/TS 22690 identifies the quality-related data for the process of the next-generation sequencing of RNA (RNA-seq). The sequencing platform covered by this document is limited to short-read sequencers. 

ISO/TS 22690 is applicable to human health associated species such as humans, cell lines, and preclinical animals.  

Note:  

• Other biological species are outside the scope of this document. 
• The use of RNA-seq for mutation detection and virus identification is outside of the scope of this document. 

From a biological point of view, expression profiles of all genetic sequences including genes, transcripts, isoforms, exons, and junctions are within the scope of this document 

Who is ISO/TS 22690 for? 

ISO/TS 22690 on genomics informatics is useful for: 

• Testing Laboratory of gene 

Why should you use ISO/TS 22690 ? 

High-quality data are the foundation for deriving reliable biological conclusions from a gene-expression study. However, large differences in data quality have been observed in published data sets when the same platform was used by different laboratories. In many cases, the poor quality of data was due not to the inherent quality problems of a platform but to the lack of technical proficiency of the laboratory that generated the data. Therefore, proficiency testing, an assessment of the overall competence performed through inter-laboratory comparisons, is introduced in ISO/TS 22690 to establish and monitor the quality of laboratory tests. 

 Adopting ISO/TS 22690 is vital: 

• To enhance the community’s understanding of the technical performance of high-throughput gene expression,  
• benefit the interoperability of qualified gene-expression data by researchers, commercial entities and regulatory bodies,  
• improve the application of high-throughput gene expression in industry and clinics, promote the acceptance of transparent reporting according to the FAIR (findable, accessible, interoperable, and reusable) data principles, and contribute to the development of precision medicine.