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MpGAP is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. It is an easy to use pipeline that adopts well known software for de novo genome assembly of Illumina, Pacbio and Oxford Nanopore sequencing data through illumina only, long reads only or hybrid modes.
This pipeline wraps up the following software:
| Source | |
|---|---|
| Assemblers | Canu, Flye, Raven, Shasta, wtdbg2, Haslr, Unicycler, Spades, Shovill, Megahit |
| Polishers | Nanopolish, Medaka, gcpp, Pilon |
| Quality check | QUAST, MultiQC |
Are you curious about changes between releases? See the changelog.
- I strongly, vividly, mightily recommend the usage of the latest versions hosted in master branch, which is nextflow's default.
- The latest will always have support, bug fixes and generally maitain the same processes (I mainly add things instead of removing) that also were in previous versions.
- But, if you really want to execute an earlier release, please see the instructions for that.
- Versions below 3.0 are no longer supported.
This pipeline has two complementary pipelines (also written in nextflow) for NGS preprocessing and prokaryotic genome annotation that can give the user a complete workflow for bacterial genomics analyses.
In the pipeline we always try to create a workflow and a execution dynamics that is the most generic possible and is suited for the most possible use cases.
Therefore, feedbacks are very well welcomed. If you believe that your use case is not encompassed in the pipeline, you have enhancement ideas or found a bug, please do not hesitate to open an issue to disscuss about it.
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Install Nextflow:
curl -s https://get.nextflow.io | bash -
Give it a try:
nextflow run fmalmeida/mpgap --help
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Download required tools
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for docker
# for docker docker pull fmalmeida/mpgap:v3.1 # run nextflow run fmalmeida/mpgap -profile docker [options]
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for singularity
# for singularity # remember to properly set NXF_SINGULARITY_LIBRARYDIR # read more at https://www.nextflow.io/docs/latest/singularity.html#singularity-docker-hub export NXF_SINGULARITY_LIBRARYDIR=MY_SINGULARITY_IMAGES # your singularity storage dir export NXF_SINGULARITY_CACHEDIR=MY_SINGULARITY_CACHE # your singularity cache dir singularity pull --dir $NXF_SINGULARITY_LIBRARYDIR fmalmeida-mpgap-v3.1.img docker://fmalmeida/mpgap:v3.1 # run nextflow run fmalmeida/mpgap -profile singularity [options]
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for conda
# for conda # it is better to create envs with mamba for faster solving wget https://github.com/fmalmeida/mpgap/raw/master/environment.yml conda env create -f environment.yml # advice: use mamba # must be executed from the base environment # This tells nextflow to load the available mpgap environment when required nextflow run fmalmeida/mpgap -profile conda [options]
🎯 Please make sure to also download its busco databases. See the explanation
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Start running your analysis
nextflow run fmalmeida/mpgap -profile <docker/singularity/conda>
🔥 Please read the documentation below on selecting between conda, docker or singularity profiles, since the tools will be made available differently depending on the profile desired.
Nextflow profiles are a set of "sensible defaults" for the resource requirements of each of the steps in the workflow, that can be enabled with the command line flag -profile. You can learn more about nextflow profiles at:
- https://nf-co.re/usage/configuration#basic-configuration-profiles
- https://www.nextflow.io/docs/latest/config.html#config-profiles
The pipeline have "standard profiles" set to run the workflows with either conda, docker or singularity using the local executor, which is nextflow's default and basically runs the pipeline processes in the computer where Nextflow is launched. If you need to run the pipeline using another executor such as sge, lsf, slurm, etc. you can take a look at nextflow's manual page to proper configure one in a new custom profile set in your personal copy of MpGAP config file and take advantage that nextflow allows multiple profiles to be used at once, e.g. -profile conda,sge.
By default, if no profile is chosen, the pipeline will try to load tools from the local machine $PATH. Available pre-set profiles for this pipeline are: docker/conda/singularity, you can choose between them as follows:
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conda
# must be executed from the base environment # This tells nextflow to load the available mpgap environment when required nextflow run fmalmeida/mpgap -profile conda [options]
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docker
nextflow run fmalmeida/mpgap -profile docker [options]
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singularity
nextflow run fmalmeida/mpgap -profile singularity [options]
📖 Please use conda as last resource
Instructions to create required conda environment are found in the installation section
The usage of conda profile will only work in linux-64 machine because some of the tools only have its binaries available for this machine, and others had to be put inside the "bin" dir to avoid version compatibility also were compiled for linux-64. A few examples are: wtdbg2, ALE (used as auxiliary tool in pilon polish step), spades v3.13 for unicycler, and others.
Therefore, be aware, -profile conda will only work on linux-64 machines. Users in orther systems must use it with docker or singularity.
Finally, the main conda packages in the environment.yml file have been "frozen" to specific versions to make env solving faster. If you saw that I tool has a new update and would like to see it updated in the pipeline, please flag an issue.
Also, since in quast 5.0.2 the automatic download of its busco databases is broken, if using conda you must download the busco dbs for quast to properly run the assembly quality check step.
CONDA_PREFIXis the base/root directory of your conda installation
# create the directory
mkdir -p $CONDA_PREFIX/envs/mpgap-3.1/lib/python3.6/site-packages/quast_libs/busco/
# bacteria db
wget -O $CONDA_PREFIX/envs/mpgap-3.1/lib/python3.6/site-packages/quast_libs/busco/bacteria.tar.gz https://busco.ezlab.org/v2/datasets/bacteria_odb9.tar.gz
# eukaryota db
wget -O $CONDA_PREFIX/envs/mpgap-3.1/lib/python3.6/site-packages/quast_libs/busco/eukaryota.tar.gz https://busco.ezlab.org/v2/datasets/eukaryota_odb9.tar.gz
# fungi db
wget -O $CONDA_PREFIX/envs/mpgap-3.1/lib/python3.6/site-packages/quast_libs/busco/fungi.tar.gz https://busco.ezlab.org/v2/datasets/fungi_odb9.tar.gz
chmod -R 777 $CONDA_PREFIX/envs/mpgap-3.1/lib/python3.6/site-packages/quast_libs/busco
# get augustus database with
# must be executed in the end because its links for bacteria, fungi and eukaryota are broken
# it is only working for augustus
conda activate mpgap-3.1 && quast-download-buscoHybrid assemblies can be produced with two available strategies. Please read more about the strategies and how to set them up in the online documentation.
➡️ they are chosen with the parameter --hybrid_strategy.
It uses the hybrid assembly modes from Unicycler, Haslr and/or SPAdes.
It produces a long reads only assembly and polishes (correct errors) it with short reads using Pilon.
If polishing with Illumina paired end reads pilon will be executed with Unicycler-polish program, taking advantage of its ability to perform multiple rounds of polishing until changes are minimal.
# run the pipeline setting the desired hybrid strategy globally (for all samples)
nextflow run fmalmeida/mpgap \
--output output \
--max_cpus 5 \
--input "samplesheet.yml" \
--hybrid_strategy "both"🔥 This will perform, for all samples, both both strategy 1 and strategy 2 hybrid assemblies. Please read more about it in the manual reference page and samplesheet reference page.
For understading pipeline usage and configuration, users must read the complete online documentation »
All parameters showed above can be, and are advised to be, set through the configuration file. When a configuration file is used the pipeline is executed as nextflow run fmalmeida/mpgap -c ./configuration-file. Your configuration file is what will tell the pipeline which type of data you have, and which processes to execute. Therefore, it needs to be correctly configured.
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To create a configuration file in your working directory:
nextflow run fmalmeida/mpgap --get_config
Nextflow has an awesome feature called NF tower. It allows that users quickly customise and set-up the execution and configuration of cloud enviroments to execute any nextflow pipeline from nf-core, github (this one included), bitbucket, etc. By having a compliant JSON schema for pipeline configuration it means that the configuration of parameters in NF tower will be easier because the system will render an input form.
Checkout more about this feature at: https://seqera.io/blog/orgs-and-launchpad/
Users can trigger a graphical and interactive pipeline configuration and execution by using nf-core launch utility. nf-core launch will start an interactive form in your web browser or command line so you can configure the pipeline step by step and start the execution of the pipeline in the end.
# Install nf-core
pip install nf-core
# Launch the pipeline
nf-core launch fmalmeida/mpgapIt will result in the following:
- Whenever using unicycler with unpaired reads, an odd platform-specific SPAdes-related crash seems do randomly happen as it can be seen in the issue discussed at rrwick/Unicycler#188.
- As a workaround, Ryan says to use the
--no_correctparameter which solves the issue and does not have a negative impact on assembly quality. - Therefore, if you run into this error when using unpaired data you can activate this workaroud with:
--unicycler_additional_parameters " --no_correct ".
- Sometimes, shovill assembler can fail and cause the pipeline to fail due to problems in estimating the genome size. This, is actually super simple to solve! Instead of letting the shovill assembler estimate the genome size, you can pass the information to it and prevent its fail:
--shovill_additional_parameters " --gsize 3m "
To cite this tool please refer to our Zenodo tag.
This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the GPLv3.
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
In addition, users are encouraged to cite the programs used in this pipeline whenever they are used. Links to resources of tools and data used in this pipeline are in the list of tools.