Standardization and quality management in next-generation sequencing

Abstract

DNA sequencing continues to evolve quickly even after > 30 years. Many new platforms suddenly appeared and former established systems have vanished in almost the same manner. Since establishment of next-generation sequencing devices, this progress gains momentum due to the continually growing demand for higher throughput, lower costs and better quality of data. In consequence of this rapid development, standardized procedures and data formats as well as comprehensive quality management considerations are still scarce. Here, we listed and summarized current standardization efforts and quality management initiatives from companies, organizations and societies in form of published studies and ongoing projects. These comprise on the one hand quality documentation issues like technical notes, accreditation checklists and guidelines for validation of sequencing workflows. On the other hand, general standard proposals and quality metrics are developed and applied to the sequencing workflow steps with the main focus on upstream processes. Finally, certain standard developments for downstream pipeline data handling, processing and storage are discussed in brief. These standardization approaches represent a first basis for continuing work in order to prospectively implement next-generation sequencing in important areas such as clinical diagnostics, where reliable results and fast processing is crucial. Additionally, these efforts will exert a decisive influence on traceability and reproducibility of sequence data.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

“…32 . When used specifically for the detection of antimicrobial resistance the benchmark resources need to include strict performance thresholds, and whether these should be set a priori along with the levels of these thresholds are subjects for consideration.…”

“…Current guidelines and recommendations place the responsibility of validating the bioinformatics pipelines (and ensuring reliability after update of any of its components) with the operator/quality manager of the test facility 32, 33, 39 . In fact, thus far, many different sets of benchmark materials and resources have been produced for local use or within collaborative endeavours (see 34).…”

“…In response to this complex state-of-the-art and the fast-moving environment in which these technologies are developing, efforts for the standardisation and development of best practices have avoided the prescription of restrictive guidelines, methods or technologies in favour of a more flexible approach emphasising quality metrics and fitness-for-purpose 32, 33 . For bioinformatics pipelines, the development of benchmark resources would play an important role in validating specific bioinformatics strategies and workflows, testing any update to the software underlying an established pipeline or allowing proficiency testing of individual laboratories 33– 35 .…”

Genome-Guided Transcriptomics, DNA-Protein Interactions, and Variant Calling

“…Most of the work done is not reproducible, and data processing pipelines could not be shared among different experiments. Although guidelines for result validation have been extensively reviewed [40][41][42][43], processing parameters should be recorded thoroughly. The complexity of the NGS experiments demands complete description of the parameters through metadata; minimum information about any (x) sequence (MIxS) creates a single-entry point to all minimum information checklists for sequence data [44].…”

Real-Time Sequencing of Mycobacterium tuberculosis: Are We There Yet?

“…However, while this resistance mutation was correctly classified by using a 3ϫ threshold, it is important to note that deeper sequencing was required to confidently exclude SNPs at 174 other loci known to be associated with resistance. Given the consequences of both false-positive and false-negative resistance calls, before WGS can be implemented in the diagnostic work flow, quality control thresholds used must therefore undergo thorough validation and ideally be standardized for reproducible clinical use (16,17).…”