basecalling

A PyTorch Basecaller for Oxford Nanopore Reads

Megalodon is a research command line tool to extract high accuracy modified base and sequence variant calls from raw nanopore reads by anchoring the information rich basecalling neural network output to a reference genome/transriptome.

Methylation/modified base calling separated from basecalling.

Research release basecalling models and configurations

Basecalling configuration prediction through FASTQ files

Python client library for Guppy

modPhred is a pipeline for detection of DNA/RNA modifications from raw ONT data

Nanopore direct RNA basecaller

[NeurIPS 2024] A Multi-task Benchmark Dataset for Nanopore Sequencing.

snakemake workflow for basecalling and demultiplexing of ONT sequencing data

A Snakemake workflow for basecalling and demultiplexing of Oxford Nanopore data using Dorado.

Quickstart to Bioinformatics & Biomedical AI.

Cost-effective and scalable Oxford Nanopore Technologies (ONT) basecalling on AWS using Dorado, Nextflow, and AWS Batch with horizontal GPU scaling

Novel basecaller, jointly processing raw and event data from ONT nanopore, basec on encoder-decoder + attention architecture

Benchmarking several NVIDIA GPUs with dorado

nanoRMS2 is a pipeline for detection of DNA/RNA modifications from raw ONT data

Nanopore Basecalling

Nextflow pipeline to process ONT adaptive sampling runs (basecalling, mapping, statistics)

A performance analysis framework for neural network-based DNA basecalling from nanopore sequencing data. Implements and benchmarks LSTM and TCN architectures with CTC decoding, featuring comprehensive signal preprocessing pipelines and accuracy-speed tradeoff analysis for real-time genomic applications.