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* add module AMPlify * Apply suggestions from code review Thanks for the review! Co-authored-by: Moritz E. Beber <midnighter@posteo.net> * removed trailing whitespaces * Apply suggestions from code review Thanks again! Co-authored-by: Moritz E. Beber <midnighter@posteo.net> * Apply suggestions from code review Thank you for the suggestions! Co-authored-by: Sateesh Peri <33637490+sateeshperi@users.noreply.github.com> Co-authored-by: James A. Fellows Yates <jfy133@gmail.com> * Apply suggestions from code review Co-authored-by: Sateesh Peri <33637490+sateeshperi@users.noreply.github.com> * including review suggestions * fix versions.yml * add model_dir input * add model_dir to meta.yml * complete faa pattern in meta.yml * add fa.gz to pattern Co-authored-by: Moritz E. Beber <midnighter@posteo.net> Co-authored-by: Sateesh Peri <33637490+sateeshperi@users.noreply.github.com> Co-authored-by: James A. Fellows Yates <jfy133@gmail.com>
47 lines
1.3 KiB
YAML
47 lines
1.3 KiB
YAML
name: "amplify_predict"
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description: AMPlify is an attentive deep learning model for antimicrobial peptide prediction.
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keywords:
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- antimicrobial peptides
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- AMPs
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- prediction
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- model
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tools:
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- "amplify":
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description: "Attentive deep learning model for antimicrobial peptide prediction"
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homepage: "https://github.com/bcgsc/AMPlify"
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documentation: "https://github.com/bcgsc/AMPlify"
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tool_dev_url: "https://github.com/bcgsc/AMPlify"
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doi: "https://doi.org/10.1186/s12864-022-08310-4"
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licence: "['GPL v3']"
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input:
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- meta:
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type: map
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description: |
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Groovy Map containing sample information
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e.g. [ id:'test', single_end:false ]
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- faa:
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type: file
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description: amino acid sequences fasta
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pattern: "*.{fa,fa.gz,faa,faa.gz,fasta,fasta.gz}"
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- model_dir:
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type: directory
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description: Directory of where models are stored (optional)
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output:
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- meta:
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type: map
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description: |
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Groovy Map containing sample information
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e.g. [ id:'test', single_end:false ]
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- versions:
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type: file
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description: File containing software versions
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pattern: "versions.yml"
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- tsv:
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type: file
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description: amino acid sequences with prediction (AMP, non-AMP) and probability scores
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pattern: "*.{tsv}"
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authors:
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- "@louperelo"
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