Diseases caused by genetic changes could be detected more readily thanks to an advance in DNA analysis software.
The development will make it easier to integrate genetic testing into health care systems such as the UK's National Health Service, which cares for around three million people affected by genetic diseases in the UK.
The new tool can spot precise genetic changes that cause disease in the more than three billion letters of DNA code that make up the human genome.
It does this by linking to a database of clinical information from people with genetic diseases to pinpoint DNA changes that are known to cause illness. The software also predicts the consequences of DNA changes, helping to identify disease-causing differences that are not already linked to a known condition.
In addition, the software scans databases of genetic information from healthy people to rule out DNA differences that look as though they may cause a disease but are harmless -minimising the risk of false diagnoses.
The sodtware shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Using only human genetic data, the software, G2P, performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.
Experts say the system is particularly useful for diagnosing disorders that may be caused by many different genes, such as severe intellectual disabilities in children.
Using genetics to diagnose diseases moved a step closer when advances in DNA sequencing technology made it affordable and possible to decode a person's genome within a few days.
The sheer volume of data produced - and shortage of expertise - has hampered efforts to analyse it and generate meaningful results.
The new system, which is freely available online, will help to overcome this bottleneck and make it easier to diagnose genetic conditions in clinical practice and in research programmes.
The research is published in Nature Communications.
Genome analysis using a new software tool
- 329 views