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Merge branch 'CW-2209-docs' into 'dev'
CW-2209 docs remove = Closes CW-2209 See merge request epi2melabs/workflows/wf-transcriptomes!114
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CHANGELOG.md

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@@ -8,6 +8,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Changed
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- Any sample aliases that contain spaces will be replaced with underscores.
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### Fixed
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- Documentation parameter examples corrected.
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## [v0.2.0]
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- GitHub issue templates

README.md

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@@ -153,24 +153,24 @@ Below are some commonly used parameters in the format used in config files.
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Select how the transcriptome used for analysis should be prepared:
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- To create a reference transcriptome using an existing reference genome `transcriptome_source = reference-guided` (default)
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- Use a a supplied transcriptome `transcriptome_source = precomputed"`
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- Gnerate transcriptome via the denovo pipeline `transcriptome_source = denovo"`
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- To create a reference transcriptome using an existing reference genome `--transcriptome_source reference-guided` (default)
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- Use a a supplied transcriptome `--transcriptome_source precomputed"`
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- Gnerate transcriptome via the denovo pipeline `--transcriptome_source denovo"`
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To run the workflow with direct RNA reads `direct_rna = false` (this just skips the pychopper step).
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To run the workflow with direct RNA reads `--direct_rna false` (this just skips the pychopper step).
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Pychopper and minimap2 can take options via `minimap2_opts` and `pychopper_opts`, for example:
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Pychopper and minimap2 can take options via `--minimap2_opts` and `--pychopper_opts`, for example:
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- When using the SIRV synthetic test data
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- `minimap2_opts = '-uf --splice-flank=no'`
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- `--minimap2_opts '-uf --splice-flank=no'`
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- pychopper needs to know which cDNA synthesis kit used, which can be specified with
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- SQK-PCS109: `pychopper_opts = '-k PCS109'` (default)
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- SQK-PCS110: `pychopper_opts = '-k PCS110'`
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- SQK-PCS111: `pychopper_opts = '-k PCS111'`
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- SQK-PCS109: `--pychopper_opts '-k PCS109'` (default)
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- SQK-PCS110: `--pychopper_opts '-k PCS110'`
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- SQK-PCS111: `--pychopper_opts '-k PCS111'`
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- pychopper can use one of two available backends for identifying primers in the raw reads
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- nhmmscan `pychopper opts = '-m phmm'`
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- edlib `pychopper opts = '-m edlib'`
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- nhmmscan `--pychopper opts '-m phmm'`
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- edlib `--pychopper opts '-m edlib'`
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__Note__: edlib is set by default in the config as it's quite a lot faster. However, it may be less sensitive than nhmmscan.
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The resulting JAFFAL reference files will look something like `hg38_genCode22.fa`. The following options enable JAFFAL to find these
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files:
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`jaffal_genome = reference_genome_name` optional (default: `hg38`)
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`jaffal_annotation = jaffal_annotation_prefix` optional (default: `genCode22`)
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`--jaffal_genome reference_genome_name` optional (default: `hg38`)
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`--jaffal_annotation jaffal_annotation_prefix` optional (default: `genCode22`)
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__Note__: JAFFAL is not currently working on Mac M1 (osx-arm64 architecture).

docs/quickstart.md

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Select how the transcriptome used for analysis should be prepared:
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- To create a reference transcriptome using an existing reference genome `transcriptome_source = reference-guided` (default)
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- Use a a supplied transcriptome `transcriptome_source = precomputed"`
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- Gnerate transcriptome via the denovo pipeline `transcriptome_source = denovo"`
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- To create a reference transcriptome using an existing reference genome `--transcriptome_source reference-guided` (default)
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- Use a a supplied transcriptome `--transcriptome_source precomputed"`
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- Gnerate transcriptome via the denovo pipeline `--transcriptome_source denovo"`
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To run the workflow with direct RNA reads `direct_rna = false` (this just skips the pychopper step).
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To run the workflow with direct RNA reads `--direct_rna false` (this just skips the pychopper step).
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Pychopper and minimap2 can take options via `minimap2_opts` and `pychopper_opts`, for example:
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Pychopper and minimap2 can take options via `--minimap2_opts` and `--pychopper_opts`, for example:
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- When using the SIRV synthetic test data
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- `minimap2_opts = '-uf --splice-flank=no'`
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- `--minimap2_opts '-uf --splice-flank=no'`
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- pychopper needs to know which cDNA synthesis kit used, which can be specified with
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- SQK-PCS109: `pychopper_opts = '-k PCS109'` (default)
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- SQK-PCS110: `pychopper_opts = '-k PCS110'`
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- SQK-PCS111: `pychopper_opts = '-k PCS111'`
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- SQK-PCS109: `--pychopper_opts '-k PCS109'` (default)
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- SQK-PCS110: `--pychopper_opts '-k PCS110'`
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- SQK-PCS111: `--pychopper_opts '-k PCS111'`
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- pychopper can use one of two available backends for identifying primers in the raw reads
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- nhmmscan `pychopper opts = '-m phmm'`
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- edlib `pychopper opts = '-m edlib'`
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- nhmmscan `--pychopper opts '-m phmm'`
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- edlib `--pychopper opts '-m edlib'`
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__Note__: edlib is set by default in the config as it's quite a lot faster. However, it may be less sensitive than nhmmscan.
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The resulting JAFFAL reference files will look something like `hg38_genCode22.fa`. The following options enable JAFFAL to find these
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`jaffal_genome = reference_genome_name` optional (default: `hg38`)
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`jaffal_annotation = jaffal_annotation_prefix` optional (default: `genCode22`)
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`--jaffal_genome reference_genome_name` optional (default: `hg38`)
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`--jaffal_annotation jaffal_annotation_prefix` optional (default: `genCode22`)
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__Note__: JAFFAL is not currently working on Mac M1 (osx-arm64 architecture).

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