assemblerflow 1.1.0.post3

A Nextflow pipeline assembler for genomics. Pick your modules. Assemble them. Run the pipeline.

Assemblerflow :whale2::package:

A Nextflow pipeline assembler for genomics. Pick your modules. Assemble them. Run the pipeline.

The premisse

Build a pipeline

What if building your own genomics pipeline would be as simple as:

assemblerflow.py build -t "trimmomatic fastqc skesa pilon" -o my_pipeline.nf

Seems pretty simple right? What if we could run this pipeline with a single command on any linux machine or cluster by leveraging the awesomeness of nextflow and docker/singularity containers without having to install any of the pipeline dependencies?

Run the pipeline

nextflow run my_pipeline.nf --fastq path/to/fastq

N E X T F L O W  ~  version 0.28.0
Launching `my_pipeline` [prickly_mcnulty] - revision: 041b7b793f

============================================================
                M Y   P I P E L I N E
============================================================
Built using assemblerflow v1.0.2

 Input FastQ                 : 2
 Input samples               : 1
 Reports are found in        : ./reports
 Results are found in        : ./results
 Profile                     : standard

Starting pipeline at Sun Apr 08 18:22:24 WEST 2018

[warm up] executor > local
[7c/eb5f2f] Submitted process > integrity_coverage_1_1 (02AR0553)
(...)
[31/7d90a1] Submitted process > compile_pilon_report_1_6

Completed at: Sun Apr 08 18:43:41 WEST 2018
Duration    : 21m 17s
Success     : true
Exit status : 0

Congratulations! You just built and executed your own pipeline with only two commands! :tada:

Installation

Assemblerflow is available as a bioconda package, which already brings nextflow:

conda install assemblerflow

Container engines

Pipelines built with assemblerflow require at least one container engine to be installed, among docker, singularity or shifter. If you already have any one of these installed, you're good to go. If not, we recommend installing singularity, which also has a bioconda package:

conda install singularity

How to use it

The complete user guide of assemblerflow can be found on readthedocs.org. For a quick and dirty demonstration, see below.

Quick guide

Building a pipeline

Assemblerflow comes with a number of ready-to-use components to build your own pipeline. Following some basic rules, such as the output type of one process must match the input type of the next process, assembling a pipeline is done using the build mode and the -t option:

assemblerflow build -t "trimmomatic spades abricate" -o my_pipeline.nf -n "assembly pipe"

This command will generate everything that is necessary to run the pipeline automatically, but the main pipeline executable file will be my_pipeline.nf. This file will contain a nextflow pipeline for genome assembly starts with trimmomatic and finishes with anti-microbial gene annotation using abricate.

Wait... what about the software parameters?

Each component in the pipeline has its own set of parameters that can be modified before or when executing the pipeline. These parameters are described in the documentation of each process and you can check the options of your particular pipeline using the help option:

nextflow my_pipeline.nf --help

N E X T F L O W  ~  version 0.28.0
Launching `my_pipeline.nf` [prickly_keller] - revision: 1b3fec5658

============================================================
                A S S E M B L Y   P I P E
============================================================
Built using assemblerflow v1.0.2


Usage:
    nextflow run my_pipeline.nf

       --fastq                     Path expression to paired-end fastq files. (default: fastq/*_{1,2}.*) (integrity_coverage)
       --genomeSize                Genome size estimate for the samples. It is used to estimate the coverage and other assembly parameters andchecks (default: 2.1) (integrity_coverage)
       --minCoverage               Minimum coverage for a sample to proceed. Can be set to0 to allow any coverage (default: 15) (integrity_coverage)
       --adapters                  Path to adapters files, if any (default: None) (trimmomatic)
       --trimSlidingWindow         Perform sliding window trimming, cutting once the average quality within the window falls below a threshold (default: 5:20) (trimmomatic)
       --trimLeading               Cut bases off the start of a read, if below a threshold quality (default: 3 (trimmomatic)
       --trimTrailing              Cut bases of the end of a read, if below a threshold quality (default: 3) (trimmomatic)
       --trimMinLength             Drop the read if it is below a specified length (default: 55) (trimmomatic)
       --spadesMinCoverage         The minimum number of reads to consider an edge in the de Bruijn graph during the assembly (default: 2) (spades)
       --spadesMinKmerCoverage     Minimum contigs K-mer coverage. After assembly only keep contigs with reported k-mer coverage equal or above this value (default: 2) (spades)
       --spadesKmers               If 'auto' the SPAdes k-mer lengths will be determined from the maximum read length of each assembly. If 'default', SPAdes will use the default k-mer lengths. (default: auto) (spades)
       --abricateDatabases         Specify the databases for abricate. (abricate)

This help message is dynamically generated depending on the pipeline you build. Since this pipeline starts with trimmomatic, which receives fastq files as input, --fastq is the default parameter for providing paired-end fastq files.

Running a pipeline

Now that we have our nextflow pipeline built, we are ready to executed it by providing input data. By default, assemblerflow pipelines will run locally and use singularity to run the containers of each component. This can be changed in multiple ways, but for convenience assemblerflow has already defined profiles for most configurations of executors and container engines.

Running a pipeline locally with singularity can be done with:

# Pattern for paired-end fastq is '<sample>_1.fastq.gz <sample>_2.fastq.gz'
nextflow run my_pipeline --fastq "path/to/fastq/*_{1,2}.*"

If you want to run a pipeline in a cluster with SLURM and singularity, just use the appropriate profile:

nextflow run my_pipeline --fastq "path/to/fastq/*_{1,2}.*" -profile slurm_sing

During the execution of the pipeline, the results and reports for each component are continuously saved to the results and reports directory, respectively.

Why not just write a Nextflow pipeline?

In many cases, building a static nextflow pipeline is sufficient for our goals. However, when building our own pipelines, we often felt the need to add dynamism to this process, particularly if we take into account how fast new tools arise and existing ones change. Our biological goals also change over time and we might need different pipelines to answer different questions. Assemblerflow makes this very easy, by having a set of pre-made and ready-to-use components that can be freely assembled.

For instance, changing the assembly software in a genome assembly pipeline becomes as easy as:

# Use spades
trimmomatic spades pilon
# Use skesa
trimmomatic skesa pilon

If you are interested in having some sort of genome annotation, simply add those components at the end, using a fork syntax:

# Run prokka and abricate at the end of the assembly
trimmomatic spades pilon (prokka | abricate)

On the other hand, if you are interest in just perform allele calling for wgMLST, simply add chewbbaca:

trimmomatic spades pilon chewbbaca

Since nextflow handles parallelism of large sets of data so well, simple pipelines of two components are also useful to build:

trimmomatic fastqc

As the number of existing components grow, so does your freedom to build pipelines.

Developer guide

Adding new components

Is there a missing component that you would like to see included? We would love to expand! You could make a component request in our issue tracker.

If you want to be part of the team, you can contribute with the code as well. Each component in assemblerflow can be independently added without having to worry about the rest of the code base. You'll just need to have some knowledge of python and nextflow. Check the developer documentation for how-to guides