Gaussian mixture model-based unsupervised nucleotide modification number detection using nanopore-sequencing readouts.

ABSTRACT:

Motivation

Nucleotide modification status can be decoded from the Oxford Nanopore Technologies nanopore-sequencing ionic current signals. Although various algorithms have been developed for nanopore-sequencing-based modification analysis, more detailed characterizations, such as modification numbers, corresponding signal levels and proportions are still lacking.

Results

We present a framework for the unsupervised determination of the number of nucleotide modifications from nanopore-sequencing readouts. We demonstrate the approach can effectively recapitulate the number of modifications, the corresponding ionic current signal levels, as well as mixing proportions under both DNA and RNA contexts. We further show, by integrating information from multiple detected modification r

SUBMITTER: Ding H 

PROVIDER: S-EPMC7723331 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature