diff options
| author | CoprDistGit <infra@openeuler.org> | 2023-05-10 08:46:02 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-10 08:46:02 +0000 |
| commit | 69721d0ca2c95fd2166aa1f2f3e7a70647efb28d (patch) | |
| tree | 8feb102f5f2b010f24c22797e69045e31b97de19 | |
| parent | e4c304797e27a16f3606a26886a536bfcf4160e1 (diff) | |
automatic import of python-nanome-jax
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-nanome-jax.spec | 589 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 591 insertions, 0 deletions
@@ -0,0 +1 @@ +/nanome-jax-2.0.11.tar.gz diff --git a/python-nanome-jax.spec b/python-nanome-jax.spec new file mode 100644 index 0000000..99011a3 --- /dev/null +++ b/python-nanome-jax.spec @@ -0,0 +1,589 @@ +%global _empty_manifest_terminate_build 0 +Name: python-nanome-jax +Version: 2.0.11 +Release: 1 +Summary: NANOME (Nanopore methylation) pipeline developed by Li Lab at The Jackson Laboratory +License: MIT License +URL: https://github.com/LabShengLi/nanome +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/32/a7/6ea7fa19724d670be02a8b72be6310d1d98a9f394e825bbd8395e94dbb87/nanome-jax-2.0.11.tar.gz +BuildArch: noarch + +Requires: python3-biopython +Requires: python3-pybedtools +Requires: python3-pandas +Requires: python3-seaborn +Requires: python3-scipy +Requires: python3-numpy +Requires: python3-statsmodels +Requires: python3-scikit-learn +Requires: python3-matplotlib +Requires: python3-jinja2 +Requires: python3-openpyxl +Requires: python3-h5py +Requires: python3-tqdm +Requires: python3-joblib +Requires: python3-psutil +Requires: python3-xgboost +Requires: python3-pytabix +Requires: python3-pysam +Requires: python3-ont-fast5-api + +%description +# NANOME pipeline (Nanopore long-read sequencing data consensus DNA methylation detection) + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +## 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 + +[comment]: <> (**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.) + + + + +**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.** + + +[comment]: <> (**Results:** We compared several 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.) + + +[comment]: <> (**Conclusions:** Our study is the first benchmark of state-of-the-art 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. ) + + + +### 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](https://github.com/LabShengLi/nanome/actions). + + +## 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](https://www.nextflow.io/) (check the installation guide from https://nf-co.re/usage/installation), and have one of below commonly used environment tool: +* [Conda](https://docs.conda.io/en/latest/miniconda.html) +* [Docker](https://docs.docker.com/get-docker) +* [Singularity](https://sylabs.io/guides/3.0/user-guide/installation.html) + +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](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 +[Clair3](https://github.com/HKU-BAL/Clair3) >=v0.1-r11 +[Whatshap](https://github.com/whatshap/whatshap) >=1.0 +[NanomethPhase bam2bis](https://github.com/vahidAK/NanoMethPhase) >= 1.0 +[GNU Parallel](https://www.gnu.org/software/parallel) >=20170422 + + +Guppy software >= 4.2.2 from [ONT (Oxford Nanopore Technologies) website](https://nanoporetech.com) + + +## 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: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md) and [Specific Usage](https://github.com/LabShengLi/nanome/blob/master/docs/SpecificUsage.md) and [NANOME options](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/nanome_params.md) for how to use NANOME pipeline. For running on CloudOS platform (e.g., google cloud), please check [Usage on CloudOS](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md#5-running-pipeline-on-cloud-computing-platform). We provide a **tutorial video** for running NANOME pipeline: + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +When you have Nextflow software, NANOME pipeline can be directly executed without any other additional installation steps: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Eval.md) 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](https://www.nextflow.io/) +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](https://github.com/LabShengLi/nanome/blob/master/docs/resources/trace_benchmark.txt.tsv), [Report](https://github.com/LabShengLi/nanome/blob/master/docs/resources/report_benchmark.pdf) and [Timeline](https://github.com/LabShengLi/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 + +Timeline figure for benchmarking experiments are below: + + + +### Pipeline DAG + + + +### NANOME report +Please check [NANOME report](https://github.com/LabShengLi/nanome/blob/master/docs/NANOME_report_html.pdf) for the sample report by NANOME pipeline. + + + + +### Haplotype-aware consensus methylations +Please check [phasing usage](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/Phasing.md). + + +### Lifebit CloudOS report +We now support running NANOME on cloud computing platform. [Lifebit](https://lifebit.ai/lifebit-cloudos/) 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](https://github.com/LabShengLi/nanome/releases). For details, please go [here](https://github.com/LabShengLi/nanome/blob/master/README.md). + + +## Contact +If you have any questions/issues/bugs, please post them on [GitHub](https://github.com/LabShengLi/nanome/issues). 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 + + +%package -n python3-nanome-jax +Summary: NANOME (Nanopore methylation) pipeline developed by Li Lab at The Jackson Laboratory +Provides: python-nanome-jax +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-nanome-jax +# NANOME pipeline (Nanopore long-read sequencing data consensus DNA methylation detection) + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +## 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 + +[comment]: <> (**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.) + + + + +**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.** + + +[comment]: <> (**Results:** We compared several 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.) + + +[comment]: <> (**Conclusions:** Our study is the first benchmark of state-of-the-art 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. ) + + + +### 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](https://github.com/LabShengLi/nanome/actions). + + +## 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](https://www.nextflow.io/) (check the installation guide from https://nf-co.re/usage/installation), and have one of below commonly used environment tool: +* [Conda](https://docs.conda.io/en/latest/miniconda.html) +* [Docker](https://docs.docker.com/get-docker) +* [Singularity](https://sylabs.io/guides/3.0/user-guide/installation.html) + +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](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 +[Clair3](https://github.com/HKU-BAL/Clair3) >=v0.1-r11 +[Whatshap](https://github.com/whatshap/whatshap) >=1.0 +[NanomethPhase bam2bis](https://github.com/vahidAK/NanoMethPhase) >= 1.0 +[GNU Parallel](https://www.gnu.org/software/parallel) >=20170422 + + +Guppy software >= 4.2.2 from [ONT (Oxford Nanopore Technologies) website](https://nanoporetech.com) + + +## 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: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md) and [Specific Usage](https://github.com/LabShengLi/nanome/blob/master/docs/SpecificUsage.md) and [NANOME options](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/nanome_params.md) for how to use NANOME pipeline. For running on CloudOS platform (e.g., google cloud), please check [Usage on CloudOS](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md#5-running-pipeline-on-cloud-computing-platform). We provide a **tutorial video** for running NANOME pipeline: + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +When you have Nextflow software, NANOME pipeline can be directly executed without any other additional installation steps: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Eval.md) 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](https://www.nextflow.io/) +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](https://github.com/LabShengLi/nanome/blob/master/docs/resources/trace_benchmark.txt.tsv), [Report](https://github.com/LabShengLi/nanome/blob/master/docs/resources/report_benchmark.pdf) and [Timeline](https://github.com/LabShengLi/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 + +Timeline figure for benchmarking experiments are below: + + + +### Pipeline DAG + + + +### NANOME report +Please check [NANOME report](https://github.com/LabShengLi/nanome/blob/master/docs/NANOME_report_html.pdf) for the sample report by NANOME pipeline. + + + + +### Haplotype-aware consensus methylations +Please check [phasing usage](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/Phasing.md). + + +### Lifebit CloudOS report +We now support running NANOME on cloud computing platform. [Lifebit](https://lifebit.ai/lifebit-cloudos/) 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](https://github.com/LabShengLi/nanome/releases). For details, please go [here](https://github.com/LabShengLi/nanome/blob/master/README.md). + + +## Contact +If you have any questions/issues/bugs, please post them on [GitHub](https://github.com/LabShengLi/nanome/issues). 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 + + +%package help +Summary: Development documents and examples for nanome-jax +Provides: python3-nanome-jax-doc +%description help +# NANOME pipeline (Nanopore long-read sequencing data consensus DNA methylation detection) + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +## 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 + +[comment]: <> (**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.) + + + + +**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.** + + +[comment]: <> (**Results:** We compared several 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.) + + +[comment]: <> (**Conclusions:** Our study is the first benchmark of state-of-the-art 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. ) + + + +### 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](https://github.com/LabShengLi/nanome/actions). + + +## 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](https://www.nextflow.io/) (check the installation guide from https://nf-co.re/usage/installation), and have one of below commonly used environment tool: +* [Conda](https://docs.conda.io/en/latest/miniconda.html) +* [Docker](https://docs.docker.com/get-docker) +* [Singularity](https://sylabs.io/guides/3.0/user-guide/installation.html) + +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](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 +[Clair3](https://github.com/HKU-BAL/Clair3) >=v0.1-r11 +[Whatshap](https://github.com/whatshap/whatshap) >=1.0 +[NanomethPhase bam2bis](https://github.com/vahidAK/NanoMethPhase) >= 1.0 +[GNU Parallel](https://www.gnu.org/software/parallel) >=20170422 + + +Guppy software >= 4.2.2 from [ONT (Oxford Nanopore Technologies) website](https://nanoporetech.com) + + +## 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: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md) and [Specific Usage](https://github.com/LabShengLi/nanome/blob/master/docs/SpecificUsage.md) and [NANOME options](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/nanome_params.md) for how to use NANOME pipeline. For running on CloudOS platform (e.g., google cloud), please check [Usage on CloudOS](https://github.com/LabShengLi/nanome/blob/master/docs/Usage.md#5-running-pipeline-on-cloud-computing-platform). We provide a **tutorial video** for running NANOME pipeline: + +[](https://www.youtube.com/watch?v=TfotM55KTVE) + +When you have Nextflow software, NANOME pipeline can be directly executed without any other additional installation steps: +```angular2html +# 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](https://github.com/LabShengLi/nanome/blob/master/docs/Eval.md) 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](https://www.nextflow.io/) +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](https://github.com/LabShengLi/nanome/blob/master/docs/resources/trace_benchmark.txt.tsv), [Report](https://github.com/LabShengLi/nanome/blob/master/docs/resources/report_benchmark.pdf) and [Timeline](https://github.com/LabShengLi/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 + +Timeline figure for benchmarking experiments are below: + + + +### Pipeline DAG + + + +### NANOME report +Please check [NANOME report](https://github.com/LabShengLi/nanome/blob/master/docs/NANOME_report_html.pdf) for the sample report by NANOME pipeline. + + + + +### Haplotype-aware consensus methylations +Please check [phasing usage](https://github.com/LabShengLi/nanome/blob/tutorial1/docs/Phasing.md). + + +### Lifebit CloudOS report +We now support running NANOME on cloud computing platform. [Lifebit](https://lifebit.ai/lifebit-cloudos/) 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](https://github.com/LabShengLi/nanome/releases). For details, please go [here](https://github.com/LabShengLi/nanome/blob/master/README.md). + + +## Contact +If you have any questions/issues/bugs, please post them on [GitHub](https://github.com/LabShengLi/nanome/issues). 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 + + +%prep +%autosetup -n nanome-jax-2.0.11 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-nanome-jax -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.11-1 +- Package Spec generated @@ -0,0 +1 @@ +42e32f097ff9f69f10b7ac2867e0bc87 nanome-jax-2.0.11.tar.gz |
