New module: Ribodetector #9209
New module: Ribodetector #9209
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| input: | ||
| tuple val(meta), path(fastq) | ||
| val length | ||
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modules/nf-core/ribodetector/main.nf
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| tuple val(meta), path("*.nonrna*.fastq.gz"), emit: fastq | ||
| tuple val(meta), path("*.log"), emit: log | ||
| path "versions.yml" , emit: versions |
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| tuple val(meta), path("*.nonrna*.fastq.gz"), emit: fastq | |
| tuple val(meta), path("*.log"), emit: log | |
| path "versions.yml" , emit: versions | |
| tuple val(meta), path("*.nonrna*.fastq.gz"), emit: fastq | |
| tuple val(meta), path("*.log") , emit: log | |
| path "versions.yml" , emit: versions |
modules/nf-core/ribodetector/main.nf
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| script: | ||
| def args = task.ext.args ?: '' | ||
| def prefix = task.ext.prefix ?: "${meta.id}" | ||
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| END_VERSIONS | ||
| """ | ||
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modules/nf-core/ribodetector/main.nf
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| touch ${prefix}.nonrna.1.fastq.gz | ||
| touch ${prefix}.nonrna.2.fastq.gz |
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nf-test doesn't like empty files with .gz as the suffix, it can give weird errors.
| touch ${prefix}.nonrna.1.fastq.gz | |
| touch ${prefix}.nonrna.2.fastq.gz | |
| echo | gzip > ${prefix}.nonrna.1.fastq.gz | |
| echo | gzip > ${prefix}.nonrna.2.fastq.gz |
| - genomics | ||
| tools: | ||
| - "ribodetector": | ||
| description: "Accurate and rapid RiboRNA sequences Detector based on deep learning" |
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| description: "Accurate and rapid RiboRNA sequences Detector based on deep learning" | |
| description: "Accurate and rapid RiboRNA sequences detector based on deep learning" |
| assertAll( | ||
| { assert process.success }, | ||
| { assert process.out.fastq }, | ||
| { assert process.out.log }, | ||
| { assert path(process.out.log[0][1]).getText().contains("Writing output non-rRNA sequences") }, | ||
| ) |
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The assertions need at least to check that the versions.yml is produced consistently.
Are the files stable too?
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Unfortunately, the output can't consistently checksumed between two runs :(
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Why not, what is changing in the fastqs?
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Is there a random seed that needs to be set?
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Unfortunately, AFAIK, the devs of Ribodetector haven't implemented a way to set the manual seed in Pytorch, so 2 different runs will give slightly different results.
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PR checklist
RiboDetector is a software developed to accurately yet rapidly detect and remove rRNA sequences from metagenomeic, metatranscriptomic, and ncRNA sequencing data.
versions.ymlfile.labelnf-core modules test <MODULE> --profile singularity