nanome-jax 2.0.11

NANOME (Nanopore methylation) pipeline developed by Li Lab at The Jackson Laboratory

NANOME pipeline (Nanopore long-read sequencing data consensus DNA methylation detection)

Highlights of NANOME pipeline

Several first highlights for NANOME

• Enables users to process terabasescale Oxford Nanopore sequencing datasets.
• Provide a one command line/web-based UI for end-to-end analyzing Nanopore sequencing methylation-callings.
• Support various platform executions: local, HPC and CloudOS, without needs for tools' installation (NANOME support docker and singularity).
• First standardized whole genome-wide evaluation framework, considering per-read and per-site performance for singletons/non-singletons, genic and intergenic regions, CpG islands/shores/shelves, different CG densities regions and repetitive regions.
• The first Nextflow based DNA methylation-calling pipeline for ONT data. Please check more articles about Nextflow based workflow technology from Nature Biotechnology: https://doi.org/10.1038/s41587-020-0439-x and https://doi.org/10.1038/nbt.3820.
• Allow add new modules/tools in simple config txt file, without need to touch the main pipeline codes, supporting rapid development and evaluation.
• Consensus of top performers by XGBoost model, allow NA values.
• Multi-modifications for 5mC and 5hmC.
• Haplotype-awared phasing and allele-specific methylation detection.

Methodology of NANOME pipeline

Fig. 1A. Survey of methylation calling tools . Timeline of publication and technological developments of Oxford Nanopore Technologies (ONT) methylation calling tools to detect DNA cytosine modifications.

Fig. 1B. Workflow for 5-methylcytosine (5mC) detection for nanopore sequencing.

CI/CD features

We use CI Automation Tools to enable the automated testing on every commit and on PRs to make sure that updates are not introducing bugs. Please check the automatic testing results on Github.

System Requirements

Hardware requirements

NANOME pipeline can be easily configured with different RAM, CPU/GPU resources schema to parallelly run methylation-calling tools. For optimal usage, we recommend running NANOME pipeline on HPC or cloud computing platform, e.g., google cloud platform (GCP). The basic hardware requirements are below:

• GPU or CPU with 2+ cores.
• RAM: 7+ GB per cpu.
• Storage using HDD or SSD. Please ensure the storage before running the pipeline.

Software requirements

NANOME pipeline uses Nextflow technology. Users only need to install Nextflow (check the installation guide from https://nf-co.re/usage/installation), and have one of below commonly used environment tool:

• Conda
• Docker
• Singularity

We provide conda, docker and singularity environments that depend on below well-known open-source packages for basecalling/methylation-calling/phasing on nanopore sequencing data:

nanopolish >=0.13.2
megalodon >=2.2.9
deepsignal >=0.1.8
ont-tombo >=1.5.1
deepmod >=0.1.3
METEORE >=1.0.0
ont-pyguppy-client-lib >=4.2.2
fast5mod >=1.0.5
Clair3 >=v0.1-r11
Whatshap >=1.0
NanomethPhase bam2bis >= 1.0
GNU Parallel >=20170422

Guppy software >= 4.2.2 from ONT (Oxford Nanopore Technologies) website

Installation

Users only need to install Nextflow (https://nf-co.re/usage/installation). NANOME execution environment will be automatically configured with the support of conda, docker or singularity containers. Below is steps for installing Nextflow:

# Install nextflow
conda install -c conda-forge -c bioconda nextflow
nextflow -v

NANOME pipeline support running with various ways in different platforms:

• Docker
• Singularity
• Conda
• Local execution: running directly on default platform
• HPC clusters with SLURM support
• Cloud computing platform, e.g., Google Cloud Platform(GCP) with google-lifesciences support

Simple usage

Please refer to Usage and Specific Usage and NANOME options for how to use NANOME pipeline. For running on CloudOS platform (e.g., google cloud), please check Usage on CloudOS. We provide a tutorial video for running NANOME pipeline:

When you have Nextflow software, NANOME pipeline can be directly executed without any other additional installation steps:

# Run NANOME via docker
nextflow run LabShengLi/nanome\
    -profile test,docker

# Run NANOME via singularity
nextflow run LabShengLi/nanome\
    -profile test,singularity

# Run NANOME for human data
nextflow run LabShengLi/nanome\
    -profile test_human,[docker/singularity]

Please note that above commands are integrated in our CI/CD test cases. Our GitHub will automatically test and report results on every commit and PRs (https://github.com/LabShengLi/nanome/actions).

We firstly proposed the standardized whole genome-wide evaluation packages, check standardized evaluation tool usage for more detail. We do not suggest evaluating on a portion of CpGs for performance comparisons.

Pipeline reports for NANOME

Benchmarking reports on our HPC using Nextflow

We constructed a set of benchmarking datasets that contain reads from 800 to about 7,200 reads for NA19240, and monitored job running timeline and resource usage on our HPC, reports generated by Nextflow workflows are: Trace file, Report and Timeline.

Our HPC hardware specifications are as follows:

• CPU: Intel(R) Xeon(R) Gold 6136 CPU @ 3.00GHz
• GPU: Tesla V100-SXM2-32GB
• RAM: 300 GB
• Slurm manager version: 19.05.5

Timeline figure for benchmarking experiments are below:

Pipeline DAG

NANOME report

Please check NANOME report for the sample report by NANOME pipeline.

Haplotype-aware consensus methylations

Please check phasing usage.

Lifebit CloudOS report

We now support running NANOME on cloud computing platform. Lifebit is a web-based cloud computing platform, and below is the running reports:

• Ecoli test report: https://cloudos.lifebit.ai/public/jobs/61c9fd328c574a01e8d31d2e
• Human test report: https://cloudos.lifebit.ai/public/jobs/61c9fe618c574a01e8d31e99
• NA12878 chr22 report: https://cloudos.lifebit.ai/public/jobs/61c4f2ad8c574a01e8d0eee3
• NA12878 chr20 part5 report: https://cloudos.lifebit.ai/public/jobs/61c770748c574a01e8d2062b

Revision History

For release history, please visit here. For details, please go here.

Contact

If you have any questions/issues/bugs, please post them on GitHub. We will continuously update the GitHub to support famous methylation-calling tools for Oxford Nanopore sequencing.

Reference

DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation. Genome Biology 22, 295 (2021). https://doi.org/10.1186/s13059-021-02510-z