Best practice recommendations for bioinformatics approaches applied to high-throughput sequencing for rare disease and cancer diagnosis within the UK National Health Service
Jamie M Ellingford, Erik Waskiewicz, Ashley J Pritchard, Javier Lopez, Rebecca Morgan, Emily Ley, Matt Lyon, Alona Sosinsky, Dalia Kasperaviciute, Joo Wook Ahn · 2026
Read Best practice recommendations for bioinformatics approaches applied to high-throughput sequencing for rare disease and cancer diagnosis within the UK National Health Service by Jamie M Ellingford, Erik Waskiewicz, Ashley J Pritchard, Javier Lopez, Rebecca Morgan, Emily Ley, Matt Lyon, Alona Sosinsky, Dalia Kasperaviciute, Joo Wook Ahn (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13479684.txt.
Description
Jamie M. Ellingford and coauthors published a 2026 best practice guide for the computer pipelines behind genomic diagnosis in the United Kingdom's National Health Service. Fast gene reading now supports rare disease and cancer diagnosis, and the software that turns raw reads into variant lists is a core part of lab work. Older national advice for this software layer was out of date.
A team of software and science staff working in NHS gene testing built the update through set talks, polls, and surveys. Their advice covers pipeline checks, quality metrics, version control, and data handling for clinical-grade work. Steady practice across labs supports fairness, since a patient's diagnosis should not depend on which center ran the sample. The guide is written for services setting up or checking their own pipelines.
Catalog record
| CREATOR | Jamie M Ellingford, Erik Waskiewicz, Ashley J Pritchard, Javier Lopez, Rebecca Morgan, Emily Ley, Matt Lyon, Alona Sosinsky, Dalia Kasperaviciute, Joo Wook Ahn |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 85808 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |