Molecular barcoding of native RNAs using nanopore sequencing and deep learning.

ABSTRACT: Nanopore sequencing enables direct measurement of RNA molecules without conversion to cDNA, thus opening the gates to a new era for RNA biology. However, the lack of molecular barcoding of direct RNA nanopore sequencing data sets severely affects the applicability of this technology to biological samples, where RNA availability is often limited. Here, we provide the first experimental protocol and associated algorithm to barcode and demultiplex direct RNA nanopore sequencing data sets. Specifically, we present a novel and robust approach to accurately classify raw nanopore signal data by transforming current intensities into images or arrays of pixels, followed by classification using a deep learning algorithm. We demonstrate the power of this strategy by developing the first experimental

SUBMITTER: Smith MA 

PROVIDER: S-EPMC7545146 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature