Nanopore links

Curated list of Nanopore tools, datasets and papers maintained by the Göke lab.

Oxford Nanopore's official forum, software downloads (Guppy, MinKNOW) and protocols. Free account required.

Oxford Nanopore's analysis platform and workflow catalogue, with example datasets.

Index of Oxford Nanopore Open Data releases: public example runs across applications and chemistries.

Raw and basecalled Open Data hosted in the AWS Open Data registry.

Bioinformatics question-and-answer site with an active Nanopore community.

Current Oxford Nanopore raw-signal format and Python/C++ API; replaces fast5.

Read, write and convert single- and multi-read fast5 files.

Community-designed compact signal format with fast random access, plus conversion tools.

Expected current level and spread per k-mer for each pore chemistry; used for event alignment and evaluation.

Documentation of fast5 attributes and the raw-to-picoampere conversion.

Oxford Nanopore's current basecaller: DNA/RNA models, modified-base calling, polyA estimation, duplex.

PyTorch research basecaller from Oxford Nanopore; the reference for training your own models.

Research release models for Dorado and Bonito, including modified-base models.

Training and inference framework for modified-base detection on top of basecalling.

Fully convolutional RNA basecaller from the research community.

Temporal convolutional network basecaller for DNA.

Standard long-read aligner; map-ont and splice presets for Nanopore DNA and RNA.

Signal-level toolkit: eventalign, polya, methylation calling.

GPU-accelerated re-implementation of Nanopolish eventalign and call-methylation.

Re-squiggle algorithm and modified-base detection on raw signal (legacy, still widely used).

Signal alignment and visualisation toolkit with DTW-based event alignment and k-mer model training.

Raw signal segmentation and event alignment for direct RNA, with modification state estimation.

Simulate raw Nanopore signal from a reference, useful for testing segmentation and basecalling.

Multiple-instance learning m6A detector on Nanopolish eventalign output.

Differential modification detection between conditions from signal distributions.

m6A and m5C detection at single-molecule resolution with CNNs.

Modification detection from basecalling error features.

Comparative signal analysis between two samples to find modified sites.

Error-of-specific-bases method; source of the eligos datasets in NanoBaseLib.

Oxford Nanopore's toolkit for summarising modified-base calls (MM/ML tags) from Dorado BAMs.

Alignment-free poly(A) tail length estimation from raw fast5 for RNA and DNA.

Read-length and quality plots for sequencing summaries, FASTQ and BAM.

Interactive QC reports from Guppy/Dorado sequencing summaries.

Sort, filter and index BAM files; the glue between every pipeline step.

Fast FASTA/FASTQ manipulation toolkit.

Nextflow pipeline for Nanopore DNA/RNA: basecalling, alignment, quantification, modification calling.

Oxford Nanopore's open-source wf-* Nextflow workflows (e.g. wf-transcriptomes, wf-human-variation).

Nextflow workflow for direct RNA preprocessing, modification and polyA analysis.

The unified six-step preprocessing pipeline used for every dataset on this site.

Direct fast5 download links and accessions for all 44 samples in NanoBaseLib.

Processed data and benchmark archives, DOI 10.5281/zenodo.10889896.

Primary archive for PRJEB/PRJNA projects; raw Nanopore submissions include fast5/pod5 tarballs.

Raw sequencing data archive; mirrors ENA submissions.

Singapore Nanopore Expression project: matched direct RNA, cDNA and short-read data for human cell lines.

Human genome and native RNA reference datasets with raw fast5.

Wang et al., Nature Biotechnology 39, 1348–1365 (2021). The standard review of the technology and its analysis landscape.

Cheng, Fu & Cheng, NeurIPS 2024 Datasets and Benchmarks Track.

Oxford Nanopore's resource centre: application notes, posters, talks and the publication database.