macrel

Predict AMPs in (meta)genomes and peptides

https://github.com/bigdatabiology/macrel

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bioinformatics biology genomics metagenomics ngless peptide
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Predict AMPs in (meta)genomes and peptides

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bioinformatics biology genomics metagenomics ngless peptide
Created over 6 years ago · Last pushed 8 months ago
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Readme Changelog License Citation

README.md

Macrel: (Meta)genomic AMP Classification and Retrieval

Pipeline to mine antimicrobial peptides (AMPs) from (meta)genomes.

Build Status Documentation Status License: MIT

Install with Bioconda Install with Bioconda

If you use this software in a publication please cite

Santos-Jnior CD, Pan S, Zhao X, Coelho LP. 2020. Macrel: antimicrobial peptide screening in genomes and metagenomes. PeerJ 8:e10555. DOI: 10.7717/peerj.10555

Run Macrel online: https://big-data-biology.org/software/macrel

License

MIT.

Macrel as a whole is under the MIT license.

Install

The recommended method of installation is through bioconda:

bash conda create --name env_macrel -c bioconda macrel conda activate env_macrel macrel -h

Alternatively, just:

bash conda install -c bioconda macrel

To install from source, read the docs

Examples

Macrel uses a subcommand interface. You run macrel COMMAND ... with the COMMAND specifying which components of the pipeline you want to use.

To run these examples, first download the example sequences from github, or by running:

bash macrel get-examples

The main output file generated by Macrel consists of a table with 6 columns containing the: sequence access code, peptide sequence, classification of peptide accordingly composition and structure, the probability associated with the AMP prediction, hemolytic activity prediction and probability associated to hemolytic activity prediction. All peptides outputted in this table are considered AMPs (p > 0.5), although peptides predicted as AMPs with probabilities closer to 1 are more likely to be active.

To run Macrel on peptides, use the peptides subcommand:

bash macrel peptides \ --fasta example_seqs/expep.faa.gz \ --output out_peptides

In this case, we use example_seqs/expep.faa.gz as the input sequence. This should be an amino-acid FASTA file. The outputs will be written into a folder called out_peptides, and Macrel will 4 threads. An example of output using this mode can be found at test/peptides/expected.prediction.

To run Macrel on contigs, use the contigs subcommand:

bash macrel contigs \ --fasta example_seqs/excontigs.fna.gz \ --output out_contigs

In this example, we use the example file excontigs.fna.gz which is a FASTA file with nucleotide sequences, writing the output to out_contigs. An example of output using this mode can be found at test/contigs/expected.prediction. Additionally to the prediction table, this mode also produces two files containing general gene prediction information in the contigs and a fasta file containing the predicted and filtered small genes ( 100 amino acids).

To run Macrel on paired-end reads, use the reads subcommand:

bash macrel reads \ -1 example_seqs/R1.fq.gz \ -2 example_seqs/R2.fq.gz \ --output out_metag \ --outtag example_metag

The paired-end reads are given as paired files (here, example_seqs/R1.fq.gz and example_seqs/R2.fq.gz). If you only have single-end reads, you can omit the -2 argument. An example of outputs using this mode can be found at test/reads/expected.prediction and test/reads/expected.smorfs.faa. Additionally to the prediction table, this mode also produces a contigs fasta file, and the two files containing general gene prediction coordinates and a fasta file containing the predicted and filtered small genes ( 100 amino acids).

To run Macrel to get abundance profiles, you only need the short reads file and a reference with peptide sequences. Use the abundance subcommand:

bash macrel abundance \ -1 example_seqs/R1.fq.gz \ --fasta example_seqs/ref.faa.gz \ --output out_abundance \ --outtag example_abundance

This mode returns a table of abundances containing two columns, the first with the name of the AMPs and the second with the number of reads mapped back to each peptide using the given reference. An example of this output using the example file can be found at test/abundances/expected.abundance.txt.

AMPSphere Querying

Macrel also supports querying the AMPSphere database (described in Santos-Jnior et al., 2024). To do so, use the query-ampsphere subcommand:

bash macrel query-ampsphere \ --fasta example_seqs/pep8.faa \ --output out_ampsphere

Note that, by default, this command requires internet access as it uses the AMPSphere API. Alternatively, you can use the --local flag to download a copy of the database and run the queries locally. This only requires the network the first time.

bash macrel query-ampsphere \ --local \ --fasta example_seqs/pep8.faa \ --output out_ampsphere

By default it performs exact matching, but you can also use MMSeqs2 to perform approximate matching by using the --query-mode=mmseqs (or --query-mode=hmm for HMMER).

Community

Macrel is actively maintained to fix all issues and assimilate suggestions we get from users (see our commitments to high-quality software).

For general questions about macrel, we ask that you use the AMPSphere Google Group (mailing list).

Technical issues can be reported using Github issues.

Owner

  • Name: Big Data Biology Lab
  • Login: BigDataBiology
  • Kind: organization
  • Email: luis@luispedro.org

GitHub Events

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  • Issue comment event: 5
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  • Pull request event: 1
  • Fork event: 4
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Last Year
  • Issues event: 2
  • Watch event: 19
  • Delete event: 2
  • Issue comment event: 5
  • Push event: 5
  • Pull request event: 1
  • Fork event: 4
  • Create event: 2

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 79 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 8
  • Total maintainers: 1
pypi.org: macrel

MACREL

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 79 Last month
Rankings
Dependent packages count: 10.1%
Dependent repos count: 21.6%
Average: 27.1%
Downloads: 49.6%
Maintainers (1)
Last synced: 6 months ago

Dependencies

setup.py pypi
  • atomicwrites *
  • pandas *
  • scikit-learn *
.github/workflows/python-app.yml actions
  • actions/checkout v3 composite
  • conda-incubator/setup-miniconda v2 composite
docs/requirements.txt pypi
  • mkdocs >=1.3.0