"NVIDIA and Harvard Researchers Use AI to Make Genome Analysis Faster And Cheaper"

Researchers from NVIDIA and Harvard have made an enormous breakthrough in genetic research by developing a deep-learning toolkit that can significantly reduce the time and cost needed to run rare and single-cell experiments. The AtacWorks toolkit can run inference on a whole genome, a process that generally takes a little over two days, in just half an hour. It's able to do so thanks to NVIDIA's Tensor Core GPUs. AtacWorks works with ATAC-seq, a well-established method designed to find open areas in the genome of healthy and diseased cells. These "open areas" are subsections of an individual's DNA used to determine and activate specific functions. This is the part of a person's genome that could give scientists indications on whether a person could have Alzheimer's, heart disease, or cancer.  ATAC-seq usually requires the analysis of tens of thousands of cells, but AtacWorks can get the same results using only tens of cells. Researchers also applied AtacWorks to a dataset of stem cells that produce red and white blood cells, subtypes that typically can't be studied using traditional methods. But with AtacWorks, they were able to identify separate parts of the DNA associated with white blood cells and red blood cells, respectively.  Researchers' ability to analyze the genome faster and cheaper will go a long way in identifying the specific mutations or biomarkers that could lead to certain diseases. It could even help drug discovery by assisting researchers to figure out how a disease works.

Engadget reports: "NVIDIA and Harvard Researchers Use AI to Make Genome Analysis Faster And Cheaper"