This repository contains a nextflow workflow
for basecalling a directory of
fast5 signal data with
and aligning it with
minimap2 to produce a sorted, indexed CRAM.
This workflow introduces users to
which is now our standard basecaller.
dorado is still under active development and
will be kept updated as new releases are made. We strongly encourage users to check
the CHANGELOG for breaking changes.
The workflow uses nextflow to manage compute and software resources, as such nextflow will need to be installed before attempting to run the workflow.
The workflow can currently be run using either Docker or Singularity to provide isolation of the required software. Both methods are automated out-of-the-box provided either Docker or Singularity is installed.
It is not required to clone or download the git repository in order to run the workflow. For more information on running EPI2ME Labs workflows visit out website.
To obtain the workflow, having installed
nextflow, users can run:
nextflow run epi2me-labs/wf-basecalling --help
to see the options and running examples for the workflow.
nextflow run epi2me-labs/wf-basecalling \ -profile singularity --input /path/to/my/fast5 \ --dorado_ext fast5 \ --ref /path/to/my/ref.fa \ --out_dir /path/to/my/outputs \ --basecaller_cfg "firstname.lastname@example.org" \ --basecaller_basemod_threads 2 \ --remora_cfg "email@example.com_5mCG@v2"
dorado repository has a table of available models to choose for
It is recommended to keep this workflow updated to take advantage of the latest basecalling models with:
nextflow pull epi2me-labs/wf-basecalling
The primary outputs of the workflow include:
<sample_name>.pass.cramcontains reads with
qscore >= threshold
<sample_name>.fail.cramcontains reads with
qscore < threshold
Take care to retain the input reference as CRAM files cannot be read without the corresponding reference!