Introduction

nf-core/multiplesequencealign is a pipeline to deploy and systematically evaluate Multiple Sequence Alignment (MSA) methods.

The pipeline 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. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!

On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the nf-core website.

1. Collect Input Information: computation of summary statistics on the input fasta file, such as the average sequence similarity across the input sequences, their length, etc. Skip by --skip_stats.
2. Guide Tree: (Optional, depends on alignment tools requirement) Renders a guide tree.
3. Align: Runs one or multiple MSA tools in parallel.
4. Evaluate: The obtained alignments are evaluated with different metrics: Sum Of Pairs (SoP), Total Column score (TC), iRMSD, Total Consistency Score (TCS), etc. Skip by --skip_eval.
5. Compress: As the final MSA files are very large, compression tools will be used before storing the final result. Skip by --skip_compress.

Available GUIDE TREE methods:

• CLUSTALO
• FAMSA

Available ALIGN methods:

• CLUSTALO
• FAMSA
• TCOFFEE
• 3DCOFFEE
• MAFFT
• KALIGN
• LEARNMSA
• MTMALIGN
• MUSCLE5

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

id,fasta,reference,structures
seatoxin,seatoxin.fa,seatoxin-ref.fa,seatoxin_structures
toxin,toxin.fa,toxin-ref.fa,toxin_structures

Each row represents a set of sequences (in this case the seatoxin and toxin protein families) to be processed.

id is the name of the set of sequences. It can correspond to the protein family name or to an internal id.

The column fasta contains the path to the fasta file that contains the sequences.

The column reference is optional and contains the path to the reference alignment. It is used for certain evaluation steps. It can be left empty.

The column structures is also optional and contains the path to the folder that contains the protein structures for the sequences to be aligned. It is used for structural aligners and certain evaluation steps. It can be left empty.

Then, you should prepare a toolsheet which defines which tools to run as follows:

toolsheet.csv:

tree,args_tree,aligner,args_aligner,
FAMSA, -gt upgma -partree, FAMSA,
, ,TCOFFEE, -output fasta_aln

tree is the tool used to build the tree.

Arguments to the tree tool can be provided using args_tree.

The aligner column contains the tool to run the alignment.

Finally, the arguments to the aligner tool can be set by using the args_alginer column.

Now, you can run the pipeline using:

nextflow run nf-core/multiplesequencealign \
   -profile test \
   --input samplesheet.csv \
   --tools toolsheet.csv \
   --outdir outdir

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/multiplesequencealign was originally written by Luisa Santus (@luisas) and Jose Espinosa-Carrasco (@JoseEspinosa) from The Comparative Bioinformatics Group at The Centre for Genomic Regulation, Spain.

The following people have significantly contributed to the development of the pipeline and its modules: Leon Rauschning (@lrauschning), Alessio Vignoli (@alessiovignoli) and Leila Mansouri (@l-mansouri).

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #multiplesequencealign channel (you can join with this invite).

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

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.