Nanopore sequencing technology can generate high-resolution transcriptomic data in real-time and at a low cost, which heralds new opportunities for molecular medicine.
We demonstrated the potential clinical utility of real-time transcriptomic profiling by processing RNA sequencing data from childhood acute lymphoblastic leukemia (ALL) clinical research samples on-the-fly with a trained neural network classifier.
Our major findings were that the neural network was able to accurately classify 11 out of 12 leukemia samples, with as little as 5 minutes of sequencing needed to accurately classify ALL.
- How gene expression profiles could be used for accurate classification of ALL molecular subtypes
- The potential impact of nanopore sequencing on the speed of ALL
- The benefits of scalability afforded by the Oxford Nanopore platform