AI clinical

The Desperate Quest for Genomic Compression Algorithms

While it’s hard to anticipate all the future benefits of genomic data, we can already see one unavoidable challenge: the nearly inconceivable amount of digital storage involved. At present the cost of storing genomic data is still just a small part of a lab’s overall budget. But that cost is growing dramatically, far outpacing the decline in the price of storage hardware. Within the next five years, the cost of storing the genomes of billions of humans, animals, plants, and microorganisms will easily hit billions of dollars per year. And this data will need to be retained for decades, if not longer.

Source: Pavlichin, D. & Weissman, T (2018). The Desperate Quest for Genomic Compression Algorithms.

Interesting article that gets into the technical details of compression technologies as a way of avoiding the storage problem that comes with the increasing digitalisation of healthcare information.

Associated with this (although not covered in this article) is the idea that we’re moving from a system in which data gathering and storage is emphasised (see any number of articles on the rise of Big Data), towards a system in which data analysis must be considered. Now that we have (or soon will have) all this data, what are we going to do with it? Unless we figure out how to use to improve healthcare then it’s pretty useless.

By Michael Rowe

I'm a lecturer in the Department of Physiotherapy at the University of the Western Cape in Cape Town, South Africa. I'm interested in technology, education and healthcare and look for places where these things meet.