Metadata-Version: 2.1
Name: nanome-jax
Version: 1.3.3
Summary: NANOME (Nanopore methylation) pipeline developed by Li Lab at The Jackson Laboratory
Home-page: https://github.com/TheJacksonLaboratory/nanome
Author: Yang Liu
Author-email: yang.liu@jax.org
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/TheJacksonLaboratory/nanome/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation
## --NANOME(Nanopore methylation) pipeline for evaluation of DNA methylation calling tools for Oxford Nanopore sequencing 

## Methodology of NANOME pipeline

**Background:** Nanopore long-read sequencing technology greatly expands the capacity of long-range, single-molecule DNA-modification detection. A growing number of analytical tools have been developed to detect DNA methylation from nanopore sequencing reads. Here, we assess the performance of different methylation calling tools to provide a systematic evaluation to guide researchers performing human epigenome-wide studies.


![Figure1A](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/Fig1A.jpg)

**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. 


![Figure1B](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/Fig1B.jpg)
**Fig. 1B. Workflow for 5-methylcytosine (5mC) detection for nanopore sequencing.** 


**Results:** We compared seven analytic tools for detecting DNA modifications from nanopore long-read sequencing data. We evaluated the CpG methylation-detection accuracy, CpG site coverage, and running time using nanopore sequencing data across different genomic contexts, using natural human DNA. Furthermore, we provide an online DNA methylation database (https://nanome.jax.org) with which to display the DNA methylation levels detected by nanopore sequencing and bisulfite sequencing data across different genomic contexts.


**Conclusions:** Our study is the first benchmark of computational methods for detection of mammalian whole-genome DNA-modifications in nanopore sequencing. We provide a broad foundation for cross-platform standardization, and an evaluation of analytical tools designed for genome-scale modified-base detection using nanopore sequencing. 

## System Requirements

### Hardware requirements

NANOME is based on Nextflow pipeline framework, and start with raw fast5 nanopore sequencing input data with a reference genome. The pipeline can be configured with different RAM, number of processors, CPU/GPU resources schema to parallel run methylation-calling tools. For optimal usage, we recommend using NANOME pipeline on HPC:
* GPU or CPU with 2+ cores. 
* RAM: 7+ GB per cpu.
* Storage using HDD or SSD. Please ensure your storage before running the pipeline.


### Software requirements
NANOME pipeline uses Nextflow technology. Users only need to install Nextflow and one of below commonly used environment tool:
* conda
* docker
* singularity

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

[nanopolish](https://github.com/jts/nanopolish) >=0.13.2  
[megalodon](https://github.com/nanoporetech/megalodon) >=2.2.9  
[deepsignal](https://github.com/bioinfomaticsCSU/deepsignal) >=0.1.8  
[ont-tombo](https://github.com/nanoporetech/tombo) >=1.5.1  
[deepmod](https://github.com/WGLab/DeepMod) >=0.1.3  
[METEORE](https://github.com/comprna/METEORE) >=1.0.0  
[ont-pyguppy-client-lib](https://github.com/nanoporetech/pyguppyclient) >=4.2.2  
[fast5mod](https://github.com/nanoporetech/fast5mod) >=1.0.5

Guppy software >= 4.2.2 from [ONT (Oxford Nanopore Technologies) website](https://nanoporetech.com)


## Installation
Users only need to install **Nextflow**, see [installation document](https://www.nextflow.io/docs/latest/getstarted.html#installation). NANOME execution environment will be automatically configured with the support of conda, docker or singularity containers.

NANOME pipeline support running with various ways in different platforms:
* Conda
    1. Create conda enviroment: `conda env create -f environment.yml`
* Docker
    1. Docker container name from [Docker Hub](https://hub.docker.com/repository/docker/liuyangzzu/nanome): `liuyangzzu/nanome:latest`, you can also build docker image by `docker build -t liuyangzzu/nanome:latest .`
* Singularity
    1. Pull image from [Docker Hub](https://hub.docker.com/repository/docker/liuyangzzu/nanome): `singularity pull docker://liuyangzzu/nanome:latest`
* HPC clusters with **SLURM** support
* Google Cloud platform with **google-lifesciences** support

## Usage
NANOME pipeline can be directly executed without any installation steps:
```angular2html
# Run NANOME using docker
nextflow run TheJacksonLaboratory/nanome\
    -profile ci,docker

# Run NANOME using singularity
nextflow run TheJacksonLaboratory/nanome\
    -profile ci,singularity
```
We provide a **5-min YouTube video** for how to run NANOME pipeline:

[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/HiNb66mwVGg/0.jpg)](https://www.youtube.com/watch?v=HiNb66mwVGg)


Please refer to [Usage](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/Usage.md) for detail usage of NANOME pipeline. For running on CloudOS platform (e.g., google cloud), please check [Usage on CloudOS](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/Usage.md#4-running-pipeline-on-cloud-computing-platform). 

If you prefer using our evaluation packages, please check [evaluation script usage](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/Eval.md) for more detail.

## Pipeline reports for NANOME
### Benchmarking reports on our HPC using [Nextflow](https://www.nextflow.io/)

We constructed a set of benchmarking datasets that contain reads from 800 to 8,000 reads for NA19240, and monitored job running timeline and resource usage on our HPC, reports generated by **Nextflow** workflows are: [Trace file](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/resources/trace_benchmark.txt.tsv), [Report](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/resources/report_benchmark.pdf)  and [Timeline](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/resources/timeline_benchmark.pdf). 

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

### Pipeline DAG
![NanomeDag](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/nanome_dag.png)

### NANOME report
Please check [NANOME report](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/NANOME_report_html.pdf) for the sample report by NANOME pipeline.

![NanomeReportHtml](https://github.com/TheJacksonLaboratory/nanome/blob/master/docs/nanome_report_html.png)



## Revision History

For release history, please visit [here](https://github.com/TheJacksonLaboratory/nanome/releases). For details, please go [here](https://github.com/TheJacksonLaboratory/nanome/blob/master/README.md).

## Contact

If you have any questions/issues/bugs, please post them on [GitHub](https://github.com/TheJacksonLaboratory/nanome/issues). We will continuously update the Github to support famous methylation-calling tools for Oxford Nanopore sequencing.

## Reference
Detailed results can be found in our preprint. Please cite our preprint below if you are interested in our GitHub repository:

 **DNA methylation calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation.** bioRxiv, 2021. Online at https://doi.org/10.1101/2021.05.05.442849.


