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Interpreting Genetic Variation

A decade after the multi-billion-dollar effort to sequence the first representative human genome, technical progress has made in sequencing whole human genomes cheaper than ever before.  This remarkable advance has brought a sea of change in human genetics, letting us tackle, at the finest resolution, key questions about how our genomes vary, and how such variation helps explain disease susceptibility.  Such research is already revealing key facets of our physiology that, until now, could be guessed at only indirectly through research on model organisms like mice.

Clinical geneticists, in particular, are using comprehensive genome sequencing to pinpoint distinctive genomic spellings, or variants,  associated with diseases.  Crucially, a consensus is emerging that the variants that strongly drive most serious diseases tend to stay rare in the population (evolution doesn’t let them become common).  Finding such culprits thus requires thoroughly sequencing individual genomes, to reveal never-before-seen variants that are simply missing from SNP chips, the panels of known common variants that offered early but limited insights in human genetic research before the era of cheap sequencing.

Each person’s genome carries a unique mix of millions of variants — and, because our population has grown explosively in the past few millennia, hundreds of thousands of variants in a given genome are indeed novel or otherwise rare.  But very few of these hundreds of thousands of potential candidates are likely to cause a particular case of disease.

As more and more people’s genomes are sequenced, the task of interpreting a genome first diagnostically, but in the long run prognostically  — has thus become a key bottleneck to scientific progress.  Quickly and reliably assessing each variant found in a given genome, to spot the one or few that matter most, takes smart computing that answers three basic questions:

  • How many sick or healthy people, in a family or the wider world, carry zero, one, or two copies of the variant or/and similar ones?
  • How does the variant affect the amount or function of particular proteins (molecules made via genomic recipes called genes)?
  • What job(s), potentially relevant to the studied disease, do those proteins do in the body?

Built to answer these three questions better than any other tool, Ingenuity Variant Analysis helps researchers quickly shortlist candidate variants and the genes and pathways that harbor them in studies of one, a few, or many human genomes.  Variant Analysis uses rich functional annotation, flexible, statistically robust genome comparison, a smart, intuitive web-based interface, and simple genome data sharing to accomplish this.