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Workflow Template - Nextflow

Template for building a small workflow in Nextflow

Background

Nextflow is a free and open source software project which makes it easier to run a computational workflow consisting of a series of interconnected steps. There are many different ways that Nextflow can be used, and the documentation can be overwhelming. This repository provides an opinionated example of how a bioinformatician can structure their code to be run using Nextflow.

Use DSL-2

After getting started, Nextflow added a lot of extremely useful functionality in a major release. Since that new functionality was not always backwards compatible, the new syntax was called "DSL-2". There is extensive documentation on the DSL-2 syntax. The only thing you need to do inside a workflow to use these features is to add nextflow.enable.dsl=2 at the top of main.nf.

It is worth your time to read over the DSL-2 documentation if you want to write workflows which are elegant and easy to maintain.

Repository Structure

The essential components of the workflow repository are:

  • main.nf: Contains the primary workflow code which pulls in all additional code from the repository
  • modules/: Contains all of the sub-workflows which are used to organize large chunks of analysis
  • templates/: Contains all of the code which is executed in each individual step of the workflow

To help you get up and running with this structure, download the minimal template directory provided in the zip archive templates/template_workflow.zip.

Parameter Inheritance

When running a workflow you can tell it what to do by passing in parameters with --param_name param_value. To make this work easily in Nextflow, make sure to set up the default value in nextflow.config in the params scope (e.g. params{param_name = 'default_value'}). If a user passes in a value, then params.param_name will have that value. If they do not, it will be default_value. The really useful thing about the params is that they are inherited by every sub-workflow and process that is invoked. In other words, without having to do anything else, I can use ${params.param_name} in one of the script files in templates/, and I know that it will contain the value that was provided by the user.

There are options to override this parameter inheritance if you want to get really fancy, but this default behavior is extremely useful if you just want to write code and not worry about explicitly piping together each of the variables into each sub-workflow as it is imported.

User Input of Parameters

There are two ways that users can most easily provide their own inputs to a workflow, with command-line flags or with a params file.

On the command line, parameters are provided using two dashes before the parameter name, e.g. --param_name value. One limitation of this approach is that the provided value will be interpreted as a string. The best example of this is the edge case of the the negative boolean (false), which will be interpreted by Nextflow as a string ('false'). The second limitation is that the command line string starts to become rather long. Another consideration of providing parameters on the command line is that they may be interpreted by the shell before execution. For example, in the context of a BASH script --param_name *.fastq.gz will first be expanded to the list of files which match that pattern (e.g., --param_name 1.fastq.gz 2.fastq.gz 3.fastq.gz), which may not be the intention. This behavior can be prevented explicitly with single-quotes in BASH, with --param_name '*.fastq.gz' being unaltered by the shell before execution.

By using a params file, the user is able to more explicitly define the set of parameters which will be provided. The params file can be formatted as JSON or YAML, with the example below shown in JSON.

{
    "param_name": "*.fastq.gz",
    "second_param": false,
    "third_param": 5
}

The params file is provided by the user with the -params-file flag. While this approach requires the user to create an additional file, it also provides a method for defining variables without worrying about the nuances of the shell interpreter.

If both methods are used for providing parameters, the command line flags will take precedence over the params file (docs).

Templates

One of the options for defining the code that is run inside a Nextflow process is to use their template syntax. The advantage of this approach is that the code can be defined in a separate file with the appropriate file extension which can be recognized by your favorite IDE and linter. Any variables from Nextflow will be interpolated using an easy ${var_name} syntax, and all other code will be native to the desired language.

The one 'gottcha' for the template structure is the backslashes are used to escape Nextflow interpolation (meaning that internal BASH variables can be specified with \$INTERNAL_VAR_NAME), and so any use of backslashes for special characters must have two backslashes. Put simply, if you want to strip the newline character in Python, you would need to write str.strip('\\n') instead of str.strip('\n').

Software Containers

Each individual step in a workflow should be run inside a container (using either Docker or Singularity) which has the required dependencies. There is a long list of public images with commonly used bioinformatics tools available at the BioContainers Registry. Specific builds should be identified from the corresponding repository for use in a workflow.

Software containers should be defined as parameters in main.nf, which allows the value to propagate automatically to all imported sub-workflows, while also being able to be overridden easily by the user if needs be.

Practically speaking, this means that every process should have a container declared which follows the pattern container "${params.container__toolname}", and which was set in nextflow.config with params{container__toolname = "quay.io/org/image:tag"}. It is crucial that the parameter be set before the subworkflows are imported, as shown in this example workflow.

Workflow Style Guide

While a workflow could be made in almost any way imaginable, there are some tips and tricks which make debugging and development easier. This is a highly opinionated list, and should be taken simply as one perspective on the topic.

  • Never use file names to encode metadata (like specimen name, .trimmed, etc.)
  • Always publish files with mode: 'copy', overwrite: true
  • Use .toSortedList() instead of .collect() for reproducible ordering
  • Add set -Eeuo pipefail to the header of any BASH script
  • Every process uses a container, which is defined as a param.container__toolname in main.nf
  • Never use .baseName to remove file extension, instead use (e.g.) .name.replaceAll('.fastq.gz', '')

Going Further

If you are interested in writing workflows in a way which can be best shared with the worldwide community of Nextflow developers, please join the nf-core community. In addition to providing a catalog of increcibly useful workflows, this group of core bioinformaticians has created an entire software suite for authoring workflows using community-driven best practices.

The nf-core codebase can be used to quickly create workflow templates (nf-core create) which are far more sophisticated and robust than this repository. The code here is for a quick-and-dirty launch into Nextflow. If you want to go deeper, connect with the other people around the world who have already put in the work to build a community, and you will go farther together.

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