| Title: |
Recommendations for bioinformatics in clinical practice |
| Authors: |
Lavrichenko, Ksenia; Engdal, Emilie S.; Marvig, Rasmus L.; Jemt, Anders; Vignes, Jone M.; Almusa, Henrikki; Saether, Kristine B.; Briem, Eiríkur; Caceres, Eva; Elvarsdóttir, Edda M.; Gíslason, Magnús H.; Haanpää, Maria K.; Henmyr, Viktor; Hotakainen, Ronja; Kaasinen, Eevi; Kanninga, Roan; Khan, Sofia; Lie-Nielsen, Mary G.; Madsen, Majbritt B.; Mähler, Niklas; Maqbool, Khurram; Neethiraj, Ramprasad; Nyrén, Karl; Paavola, Minna; Pruisscher, Peter; Sheng, Ying; Singh, Ashish K.; Srivastava, Aashish; Stautland, Thomas K.; Andreasen, Daniel T.; de Boer, Esmee t. B.; Vang, Søren; Wirta, Valtteri; Bagger, Frederik O. |
| Publication Year: |
2025 |
| Collection: |
Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto |
| Description: |
Background Next-generation sequencing (NGS) is well established in clinical diagnostics, and whole-genome sequencing (WGS) is increasingly becoming the method of choice, as a result of lower prices and robust comprehensive data. While guidelines exist for variant interpretation and laboratory quality considerations, there remains a need for standardised bioinformatics practices to ensure clinical consensus, accuracy, reproducibility and comparability. Methods This article presents consensus recommendations developed by 13 clinical bioinformatics units participating in the Nordic Alliance for Clinical Genomics (NACG) by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations. Results Key recommendations include adopting the hg38 genome build as reference, and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics in production should operate at standards similar to ISO 15189, utilising off-grid clinical-grade high-performance computing systems, standardised file formats and strict version control. Reproducibility should be ensured through containerised software environments. Pipelines must be documented and tested for accuracy and reproducibility, minimally covering unit, integration and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of real human samples that have been previously tested using a validated method. Data integrity must be verified using file hashing, while sample identity must be confirmed through fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
Genome Medicine. 2025 Oct 17;17(1):124; https://hdl.handle.net/10138/602913 |
| DOI: |
10.1186/s13073-025-01543-4 |
| Availability: |
https://hdl.handle.net/10138/602913; https://doi.org/10.1186/s13073-025-01543-4 |
| Rights: |
The Author(s) |
| Accession Number: |
edsbas.997BDD4F |
| Database: |
BASE |