bacannot pipeline

A generic but comprehensive bacterial annotation pipeline

About

Bacannot is an easy to use nextflow docker-based pipeline that adopts state-of-the-art software for prokaryotic genome annotation. It is a wrapper around several tools that enables a better understanding of prokaryotic genomes.

Its main steps are:

🎯 In order to increase the accuracy of prokka annotation, this pipeline includes an additional HMM database to prokka's defaults. It can be either TIGRFAM (smaller but curated) or PGAP (bigger comprehensive NCBI database that contains TIGRFAM).

Release notes

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 2.0 are no longer supported.

Further reading and complementary analyses

Moreover, this pipeline has two complementary pipelines (also written in nextflow) for NGS preprocessing and Genome assembly that can give the user a more thorough and robust workflow for bacterial genomics analyses.

Requirements

• Unix-like operating system (Linux, macOS, etc)
  • Windows users maybe can execute it using the linux subsystem for windows as shown in:
    • https://docs.microsoft.com/pt-br/windows/wsl/install-win10
    • https://www.nextflow.io/docs/latest/getstarted.html
    • https://en.wikipedia.org/wiki/Windows_Subsystem_for_Linux
• Java 8
• Nextflow
• Docker

These images have been kept separate to not create massive Docker image and to avoid dependencies conflicts.

Installation

1. If you don't have it already install Docker in your computer.

   • After installed, you need to download the required Docker images

   docker pull fmalmeida/bacannot:v3.1_misc    ;
   docker pull fmalmeida/bacannot:v3.1_perlenv ;
   docker pull fmalmeida/bacannot:v3.1_pyenv   ;
   docker pull fmalmeida/bacannot:v3.1_renv    ;
   docker pull fmalmeida/bacannot:jbrowse      ;

🔥 Nextflow can also automatically handle images download on the fly when executed. If docker has exceeded its download limit rates, please try again in a few hours.

2. Install Nextflow (version 20.10 or higher):

   curl -s https://get.nextflow.io | bash
   

3. Give it a try:

   nextflow run fmalmeida/bacannot -profile docker --help
   

🔥 To run the pipeline now users need to pass the -profile docker or -profile singularity parameter explicitely. The pipeline does not load it automatically anymore.

🔥 Users can get let the pipeline always updated with: nextflow pull fmalmeida/bacannot

Downloading and updating databases

Bacannot databases are not inside the docker images anymore to avoid huge images and problems with conexions and limit rates with dockerhub.

To get a copy of required bacannot databases users must:

# Download pipeline databases
nextflow run fmalmeida/bacannot --get_dbs --output bacannot_dbs -profile <docker/singularity>

This will produce a directory like this:

bacannot_dbs
├── amrfinder_db
├── antismash_db
├── argminer_db
├── card_db
├── iceberg_db
├── kofamscan_db
├── mlst_db
├── phast_db
├── phigaro_db
├── pipeline_info
├── plasmidfinder_db
├── platon_db
├── prokka_db
├── resfinder_db
├── vfdb_db
└── victors_db

To update databases you can either download a new one to a new directory. Remove the database you want to get a new one from the root bacannot dir and use the same command above to save in the same directory (the pipeline will only try to download missing databases). Or, you can use the parameter --force_update to download everything again.

Quickstart

Please refer to the quickstart page »

Overview of outputs

A nice overview of the output directory structure and the main tools/features produced by the pipeline is provided at https://bacannot.readthedocs.io/en/latest/outputs.

Documentation

Usage

Users are advised to read the complete documentation »

• Complete command line explanation of parameters:
  • nextflow run fmalmeida/bacannot --help

Command line usage examples

Command line executions are exemplified in the manual.

Using the configuration file

All the parameters showed above can be, and are advised to be, set through the configuration file. When a configuration file is set the pipeline is run by simply executing nextflow run fmalmeida/bacannot -c ./configuration-file

Your configuration file is what will tell to the pipeline the type of data you have, and which processes to execute. Therefore, it needs to be correctly set up.

Create a configuration file in your working directory:

  nextflow run fmalmeida/bacannot --get_config

Interactive graphical configuration and execution

Via NF tower launchpad (good for cloud env execution)

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/

Via nf-core launch (good for local execution)

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/bacannot

It will result in the following:

Known issues

1. Sometimes when navigating through the shiny parser the reports and JBrowse tabs may still be pointing to old, or just different, samples that have been analysed before and not the actual sample in question. For example, you open the shiny server for the Sample 2, but the reports and JBrowse are showing results of Sample 1. This is caused by the browser's data storages and cookies.
   • To solve this problem user's can just clear the cookies and data cache from the browser.
2. The JBrowse wrapper in the shiny server is not capable of displaying the GC content and methylation plots when available. It can only display the simpler tracks. If the user wants to visualise and interrogate the GC or methylation tracks it must open the JBrowse outside from the shiny server. For that, two options are available:
   • You can navigate to the jbrowse directory under your sample's output folder and simply execute http-server. This command can be found at: https://www.npmjs.com/package/http-server
   • Or, you can download the JBrowse Desktop app and, from inside the app, select the folder jbrowse/data that is available in your sample's output directory.

Citation

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.