A PyTorch Basecaller for Oxford Nanopore Reads
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Updated
Jul 25, 2024 - Python
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.
SARS-CoV-2 workflow for nanopore sequence data
Research release basecalling models and configurations
A small bash script that automates sweeping Guppy parameters in an attempt to optimise basecalling rate
Nanopore direct RNA basecaller
Novel basecaller, jointly processing raw and event data from ONT nanopore, basec on encoder-decoder + attention architecture
snakemake workflow for basecalling and demultiplexing of ONT sequencing data
modPhred is a pipeline for detection of DNA/RNA modifications from raw ONT data
My PhD thesis
Rapid comprehensive adaptive nanopore-sequencing of CNS tumours set-up and analysis pipeline
Impact of lossy compression of nanopore raw signal data on basecall and consensus accuracy
Dorado-basecalled reads improve old bacterial genome assembly
The first work to provide a comprehensive survey of a prominent set of algorithmic improvement and hardware acceleration efforts for the entire genome analysis pipeline used for the three most prominent sequencing data, short reads (Illumina), ultra-long reads (ONT), and accurate long reads (HiFi). Described in arXiv (2022) by Alser et al. https…
Quickstart to Bioinformatics & Biomedical AI.
Benchmarking several NVIDIA GPUs with dorado
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