refactoring clinical research split#485
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…into filter_vep_fix
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Nice work! Output file documention needs to updated.. Other than that everything looks good 👍🏻 |
ramprasadn
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Jan 25, 2024
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| [filter_vep from VEP](https://www.ensembl.org/info/docs/tools/vep/script/vep_filter.html) is used to subset the variants based on a list of HGNC ID:s. Typpical use case is that you want to filter your results to only include variants in a predefined set of clinically relevant genes. This step is optional and can be disabled by using the flag `--skip_vep_filter`. You will always get the complete VCF together with the clinical VCF. | |
| [filter_vep from VEP](https://www.ensembl.org/info/docs/tools/vep/script/vep_filter.html) is used to subset the variants based on a list of HGNC ID:s. Typical use case is that you want to filter your results to only include variants in a predefined set of clinically relevant genes. This step is optional and can be disabled by using the flag `--skip_vep_filter`. You will always get the complete VCF together with the clinical VCF. |
| @@ -471,28 +471,32 @@ We recommend using vcfanno to annotate SNVs with precomputed CADD scores (files | |||
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| [GENMOD](https://github.com/Clinical-Genomics/genmod) is a simple to use command line tool for annotating and analyzing genomic variations in the VCF file format. GENMOD can annotate genetic patterns of inheritance in vcf:s with single or multiple families of arbitrary size. Each variant variant will be asigned a predictded pathogenicity score. The score will be given both as a raw score and a normalized score with values between 0 and 1. The tags in the INFO field are `RankScore` and `RankScoreNormalized`. The score can be configured to fit your annotations and preferences by modifying the score config file. | |
| [GENMOD](https://github.com/Clinical-Genomics/genmod) is a simple to use command line tool for annotating and analyzing genomic variations in the VCF file format. GENMOD can annotate genetic patterns of inheritance in vcf:s with single or multiple families of arbitrary size. Each variant will be assigned a predicted pathogenicity score. The score will be given both as a raw score and a normalized score with values between 0 and 1. The tags in the INFO field are `RankScore` and `RankScoreNormalized`. The score can be configured to fit your annotations and preferences by modifying the score config file. |
| mode: params.publish_dir_mode, | ||
| saveAs: { filename -> filename.equals('versions.yml') ? null : filename } | ||
| ] | ||
| ext.prefix = { "${meta.id}_sv_csq_pli_${meta.set}" } |
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Since we are not publishing these files anymore, their description needs to be removed from output.md file
| mode: params.publish_dir_mode, | ||
| saveAs: { filename -> filename.equals('versions.yml') ? null : filename } | ||
| ] | ||
| ext.prefix = { "${meta.id}_snv_csq_pli_${meta.set}" } |
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same as sv.. needs to be removed from output.md
| mode: params.publish_dir_mode, | ||
| saveAs: { filename -> filename.equals('versions.yml') ? null : filename } | ||
| ] | ||
| ext.prefix = { "${meta.id}_mt_csq_pli_${meta.set}" } |
ramprasadn
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Jan 25, 2024
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Sorry! Approved by mistake
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No worries, your comments have been adressed :) |
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PR checklist
nf-core lint).nextflow run . -profile test,docker --outdir <OUTDIR>).nextflow run . -profile test_one_sample,docker --outdir <OUTDIR>).docs/usage.mdis updated.docs/output.mdis updated.CHANGELOG.mdis updated.README.mdis updated (including new tool citations and authors/contributors).