ontresearch/medaka repository overview

⁠Medaka

medaka is a tool to create consensus sequences and variant calls from nanopore sequencing data. This task is performed using neural networks applied a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods operating on basecalled data, and can be competitive with state-of-the-art signal-based methods whilst being much faster.

© 2018- Oxford Nanopore Technologies Ltd.

⁠Features

• Requires only basecalled data. (.fasta or .fastq)
• Improved accurary over graph-based methods (e.g. Racon).
• 50X faster than Nanopolish (and can run on GPUs).
• Benchmarks are provided here⁠.
• Includes extras for implementing and training bespoke correction networks.
• Works on Linux and MacOS.
• Open source (Mozilla Public License 2.0).

For creating draft assemblies we recommend Flye⁠.

Documentation can be found at https://nanoporetech.github.io/medaka/⁠.

Using Docker

The source code repository contains a Dockerfile which can be used to create a GPU compatible Docker container image with the appropriate CUDA and cuDNN library versions for running medaka. The image is built on top of images provided by NVIDIA⁠ designed to run with the NVIDIA Container Toolkit⁠. With the toolkit setup on your host computer the following command can be used to run the latest version of medaka:

docker run --rm --gpus 0 ontresearch/medaka:latest medaka --help

(The --gpus option can be amended as appropriate for your environment). Versioned tags are also available.