Genetic filtering: Informatics indexes spurious mutants

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  • Published: Jan 15, 2016
  • Author: David Bradley
  • Channels: Chemometrics & Informatics
thumbnail image: Genetic filtering: Informatics indexes spurious mutants

Accentuate the false positives

Shaking glowsticks photo by David Bradley. Not all mutants are bad, even in genetic diseases it's only 1 or 2 mutations out of possibly thousands that are problematic, new filtering algorithm offers improved

In genetic diseases it is only 1 or 2 mutations out of possibly thousands that appear to be problematic in the disease. Now, a new filtering algorithm offers improved "needle in a haystack" searching to exclude the problematic false positives.

A new tool, designed by scientists in the laboratory of Jean-Laurent Casanova at Rockefeller University in New York, with colleagues in France, the UK and elsewhere in the USA, can be used to predict whether a given human gene is likely to harbour disease-causing mutations. The researchers anticipate that the tool will allow geneticists and others to filter out irrelevant genes before beginning a particular disease investigation.

"To find a needle in the haystack, it helps to get rid of some of the hay," explains Yuval Itan, the study's senior author, provided you can discard that hay without throwing away the needle with it. "Filtering out the noise, the genes that pollute the data, is crucial," he adds.

Next-gen sequencing

Their analysis of the genome revealed that almost two out of every three, 58 percent, of rare genetic variants are actually located in only 2 percent of human genes. The development of the Gene Damage Index emerged from this perhaps rather surprising observation as the researchers realised that although genes are frequently mutated in the general population they are unlikely to cause inherited and rare diseases, because variations to these genes are so often also found in healthy people.

The team explains in the journal Proceedings of the National Academy of Sciences (USA) how their Gene Damage Index metric takes into account how much the gene is mutated in the general population, a factor they refer to as the "accumulated mutational damage." The calculation then includes how important a given gene is to a specific disease group, including Mendelian disorders, cancer, autism, and primary immunodeficiencies. The researchers explain that a protein-coding exome of a patient with a monogenic disease can contain some 20,000 variants, just one or two of which will give rise to symptoms of the disease. The new index essentially removes the multitude of false positives from the masses of data. "With this method, up to 60 percent of the irrelevant variants can be removed," Itan explains. "The Gene Damage Index will help scientists more easily sort through the large amounts of data produced by next-generation sequencing."

Subtle selection

The team further explains the subtleties of the GDI in their paper: "We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogues," they explain. They also discuss comparisons of the GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and showed that GDI is the most effective at removing exome variants in genes irrelevant to disease. Genic intolerance and de novo excess approaches work better for finding true positives.

The GDI server, data, and software are freely available to non-commercial users at GDI.

Related Links

Proc Natl Acad Sci (USA) 2015, 112, 13615–13620: "The human gene damage index as a gene-level approach to prioritizing exome variants"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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