Resource Centre
Video 
Untangling heterogeneity in DNA replication with nanopore sequencing
Bioinformatics tool 
Towards inferring nanopore sequencing ionic currents from nucleotide chemical structures
Bioinformatics tool 
tailfindr: Alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing
Publication 
SquiggleKit: A toolkit for manipulating nanopore signal data
Bioinformatics tool 
Sequoia: An interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets
Publication 
Real-time, direct classification of nanopore signals with SquiggleNet
Publication 
Ready-to-use nanopore platform for the detection of any DNA/RNA oligo at attomole range using an Osmium tagged complementary probe
Bioinformatics tool 
RabbitQC: high-speed scalable quality control for sequencing data
Bioinformatics tool 
PyPore: a python toolbox for nanopore sequencing data handling
Bioinformatics tool 
pycoQC, interactive quality control for Oxford Nanopore Sequencing
Bioinformatics tool 
Poretools: a toolkit for analyzing nanopore sequence data
Bioinformatics tool 
poRe: an R package for the visualization and analysis of nanopore sequencing data
Bioinformatics tool 
poRe GUIs for parallel and real-time processing of MinION sequence data
Bioinformatics tool 
Porcupine: Rapid and robust tagging of physical objects using nanopore-orthogonal DNA strands
Bioinformatics tool 
Picopore: A tool for reducing the size of Oxford Nanopore Technologies' datasets without losing information.
Publication 
Performance of neural network basecalling tools for Oxford Nanopore sequencing
Bioinformatics tool 
Penguin: a tool for predicting pseudouridine sites in direct RNA Nanopore sequencing data
Bioinformatics tool 
PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores
Publication 
Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms
Publication 
NanoReviser: an error-correction tool for Nanopore sequencing based on a deep learning algorithm