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DeepBGC: tiny revisiosn (#2070)
* Fix variable prodigal_tf * Remove tag in main.nf + tiny suggestions in ymls Co-authored-by: louperelo <44900284+louperelo@users.noreply.github.com>
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parent
8372df6fb2
commit
e55012ff92
3 changed files with 18 additions and 18 deletions
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@ -1,5 +1,4 @@
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process DEEPBGC_DOWNLOAD {
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process DEEPBGC_DOWNLOAD {
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tag "download"
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label 'process_low'
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label 'process_low'
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conda (params.enable_conda ? "bioconda::deepbgc=0.1.30" : null)
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conda (params.enable_conda ? "bioconda::deepbgc=0.1.30" : null)
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@ -8,8 +7,8 @@ process DEEPBGC_DOWNLOAD {
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'quay.io/biocontainers/deepbgc:0.1.30--pyhb7b1952_1' }"
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'quay.io/biocontainers/deepbgc:0.1.30--pyhb7b1952_1' }"
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output:
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output:
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path "deepbgc_db/" , emit: db
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path "deepbgc_db/" , emit: db
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path "versions.yml" , emit: versions
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path "versions.yml" , emit: versions
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when:
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when:
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task.ext.when == null || task.ext.when
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task.ext.when == null || task.ext.when
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@ -1,13 +1,13 @@
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name: "deepbgc_download"
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name: "deepbgc_download"
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description: database to detect BGCs in bacterial and fungal genomes using deep learning
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description: Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.
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keywords:
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keywords:
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- database
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- database
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- download
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- download
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- BGC
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- BGC
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- Biosynthetic Gene Cluster
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- biosynthetic gene cluster
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- deep learning
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- deep learning
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- neural network
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- neural network
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- random forrest
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- random forest
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- genomes
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- genomes
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- bacteria
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- bacteria
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- fungi
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- fungi
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@ -27,8 +27,8 @@ output:
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pattern: "versions.yml"
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pattern: "versions.yml"
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- deepbgc_db:
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- deepbgc_db:
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type: directory
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type: directory
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description: contains files of reference db from 'deepbgc download'
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description: Contains reference database files
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pattern: "*db"
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pattern: "deepbgc_db"
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authors:
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authors:
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- "@louperelo"
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- "@louperelo"
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@ -1,7 +1,8 @@
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name: "deepbgc_pipeline"
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name: "deepbgc_pipeline"
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description: detect BGCs in bacterial and fungal genomes using deep learning
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description: DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.
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keywords:
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keywords:
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- Biosynthetic Gene Cluster
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- BGC
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- biosynthetic gene cluster
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- deep learning
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- deep learning
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- neural network
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- neural network
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- random forest
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- random forest
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@ -48,15 +49,15 @@ output:
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pattern: "*.{txt}"
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pattern: "*.{txt}"
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- json:
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- json:
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type: file
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type: file
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description: AntiSMASH JSON file for sideloading.
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description: AntiSMASH JSON file for sideloading
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pattern: "*.{json}"
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pattern: "*.{json}"
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- bgc_gbk:
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- bgc_gbk:
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type: file
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type: file
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description: Sequences and features of all detected BGCs in GenBank format.
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description: Sequences and features of all detected BGCs in GenBank format
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pattern: "*.{bgc.gbk}"
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pattern: "*.{bgc.gbk}"
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- bgc_tsv:
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- bgc_tsv:
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type: file
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type: file
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description: Table of detected BGCs and their properties.
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description: Table of detected BGCs and their properties
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pattern: "*.{bgc.tsv}"
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pattern: "*.{bgc.tsv}"
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- full_gbk:
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- full_gbk:
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type: file
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type: file
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@ -64,23 +65,23 @@ output:
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pattern: "*.{full.gbk}"
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pattern: "*.{full.gbk}"
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- pfam_tsv:
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- pfam_tsv:
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type: file
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type: file
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description: Table of Pfam domains (pfam_id) from given sequence (sequence_id) in genomic order, with BGC detection scores.
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description: Table of Pfam domains (pfam_id) from given sequence (sequence_id) in genomic order, with BGC detection scores
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pattern: "*.{pfam.tsv}"
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pattern: "*.{pfam.tsv}"
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- bgc_png:
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- bgc_png:
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type: file
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type: file
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description: Detected BGCs plotted by their nucleotide coordinates.
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description: Detected BGCs plotted by their nucleotide coordinates
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pattern: "*.{bgc.png}"
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pattern: "*.{bgc.png}"
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- pr_png:
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- pr_png:
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type: file
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type: file
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description: Precision-Recall curve based on predicted per-Pfam BGC scores.
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description: Precision-Recall curve based on predicted per-Pfam BGC scores
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pattern: "*.{pr.png}"
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pattern: "*.{pr.png}"
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- roc_png:
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- roc_png:
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type: file
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type: file
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description: ROC curve based on predicted per-Pfam BGC scores.
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description: ROC curve based on predicted per-Pfam BGC scores
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pattern: "*.{roc.png}"
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pattern: "*.{roc.png}"
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- score_png:
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- score_png:
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type: file
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type: file
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description: BGC detection scores of each Pfam domain in genomic order.
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description: BGC detection scores of each Pfam domain in genomic order
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pattern: "*.{score.png}"
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pattern: "*.{score.png}"
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authors:
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authors:
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