Analysis of nanopore data using hidden Markov models.

ABSTRACT:

Motivation

Nanopore-based sequencing techniques can reconstruct properties of biosequences by analyzing the sequence-dependent ionic current steps produced as biomolecules pass through a pore. Typically this involves alignment of new data to a reference, where both reference construction and alignment have been performed by hand.

Results

We propose an automated method for aligning nanopore data to a reference through the use of hidden Markov models. Several features that arise from prior processing steps and from the class of enzyme used can be simply incorporated into the model. Previously, the M2MspA nanopore was shown to be sensitive enough to distinguish between cytosine, methylcytosine and hydroxymethylcytosine. We validated our automated methodology on a subset of that

SUBMITTER: Schreiber J 

PROVIDER: S-EPMC4553831 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature