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Copy file name to clipboardExpand all lines: CHANGELOG.md
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- Remove `def` from `nextflow.config` and add `trace_report_suffix` param ([#3296](https://github.com/nf-core/tools/pull/3296))
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- Move `includeConfig 'conf/modules.config'` next to `includeConfig 'conf/base.config'` to not overwrite tests profiles configurations ([#3301](https://github.com/nf-core/tools/pull/3301))
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- Use `params.monochrome_logs` in the template and update nf-core components ([#3310](https://github.com/nf-core/tools/pull/3310))
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- Fix some typos and improve writing in `usage.md` and `CONTRIBUTING.md` ([#3302](https://github.com/nf-core/tools/pull/3302))
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- Add `manifest.contributors` to `nextflow.config` ([#3311](https://github.com/nf-core/tools/pull/3311))
Copy file name to clipboardExpand all lines: nf_core/pipeline-template/.github/CONTRIBUTING.md
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# {{ name }}: Contributing Guidelines
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# `{{ name }}`: Contributing Guidelines
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Hi there!
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Many thanks for taking an interest in improving {{ name }}.
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- On your own fork, make a new branch `patch` based on `upstream/master`.
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- Fix the bug, and bump version (X.Y.Z+1).
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-A PR should be made on`master`from patch to directly this particular bug.
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-Open a pull-request from `patch` to`master`with the changes.
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{% if is_nfcore -%}
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## Pipeline contribution conventions
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To make the {{ name }} code and processing logic more understandable for new contributors and to ensure quality, we semi-standardise the way the code and other contributions are written.
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To make the `{{ name }}` code and processing logic more understandable for new contributors and to ensure quality, we semi-standardise the way the code and other contributions are written.
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### Adding a new step
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If you wish to contribute a new step, please use the following coding standards:
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1. Define the corresponding input channel into your new process from the expected previous process channel
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1. Define the corresponding input channel into your new process from the expected previous process channel.
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2. Write the process block (see below).
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3. Define the output channel if needed (see below).
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4. Add any new parameters to `nextflow.config` with a default (see below).
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### Default values
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Parameters should be initialised / defined with default values in `nextflow.config` under the `params` scope.
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Parameters should be initialised / defined with default values within the `params` scope in `nextflow.config`.
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Once there, use `nf-core pipelines schema build` to add to `nextflow_schema.json`.
Copy file name to clipboardExpand all lines: nf_core/pipeline-template/docs/usage.md
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Pipeline settings can be provided in a `yaml` or `json` file via `-params-file <file>`.
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:::warning
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Do not use `-c <file>` to specify parameters as this will result in errors. Custom config files specified with `-c` must only be used for [tuning process resource specifications](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources), other infrastructural tweaks (such as output directories), or module arguments (args).
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:::
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> [!WARNING]
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> Do not use `-c <file>` to specify parameters as this will result in errors. Custom config files specified with `-c` must only be used for [tuning process resource specifications](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources), other infrastructural tweaks (such as output directories), or module arguments (args).
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The above pipeline run specified with a params file in yaml format:
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### Reproducibility
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It is a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since.
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It is a good idea to specify the pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since.
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First, go to the [{{ name }} releases page](https://github.com/{{ name }}/releases) and find the latest pipeline version - numeric only (eg. `1.3.1`). Then specify this when running the pipeline with `-r` (one hyphen) - eg. `-r 1.3.1`. Of course, you can switch to another version by changing the number after the `-r` flag.
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This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. {% if multiqc %}For example, at the bottom of the MultiQC reports.{% endif %}
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To further assist in reproducibility, you can use share and reuse [parameter files](#running-the-pipeline) to repeat pipeline runs with the same settings without having to write out a command with every single parameter.
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:::tip
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If you wish to share such profile (such as upload as supplementary material for academic publications), make sure to NOT include cluster specific paths to files, nor institutional specific profiles.
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> [!TIP]
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> If you wish to share such profile (such as upload as supplementary material for academic publications), make sure to NOT include cluster specific paths to files, nor institutional specific profiles.
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## Core Nextflow arguments
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:::note
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These options are part of Nextflow and use a _single_ hyphen (pipeline parameters use a double-hyphen).
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:::
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> [!NOTE]
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> These options are part of Nextflow and use a _single_ hyphen (pipeline parameters use a double-hyphen)
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### `-profile`
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Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments.
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Several generic profiles are bundled with the pipeline which instruct the pipeline to use software packaged using different methods (Docker, Singularity, Podman, Shifter, Charliecloud, Apptainer, Conda) - see below.
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:::info
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We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported.
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:::
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> [!IMPORTANT]
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> We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported.
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{%- if nf_core_configs %}
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The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to see if your system is available in these configs please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).
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The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to check if your system is suported, please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).
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{% else %}
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{% endif %}
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Note that multiple profiles can be loaded, for example: `-profile test,docker` - the order of arguments is important!
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### Resource requests
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Whilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with any of the error codes specified [here](https://github.com/nf-core/rnaseq/blob/4c27ef5610c87db00c3c5a3eed10b1d161abf575/conf/base.config#L18) it will automatically be resubmitted with higher requests (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped.
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Whilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the pipeline steps, if the job exits with any of the error codes specified [here](https://github.com/nf-core/rnaseq/blob/4c27ef5610c87db00c3c5a3eed10b1d161abf575/conf/base.config#L18) it will automatically be resubmitted with higher resources request (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped.
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To change the resource requests, please see the [max resources](https://nf-co.re/docs/usage/configuration#max-resources) and [tuning workflow resources](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources) section of the nf-core website.
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### Custom Containers
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In some cases you may wish to change which container or conda environment a step of the pipeline uses for a particular tool. By default nf-core pipelines use containers and software from the [biocontainers](https://biocontainers.pro/) or [bioconda](https://bioconda.github.io/) projects. However in some cases the pipeline specified version maybe out of date.
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In some cases, you may wish to change the container or conda environment used by a pipeline steps for a particular tool. By default, nf-core pipelines use containers and software from the [biocontainers](https://biocontainers.pro/) or [bioconda](https://bioconda.github.io/) projects. However, in some cases the pipeline specified version maybe out of date.
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To use a different container from the default container or conda environment specified in a pipeline, please see the [updating tool versions](https://nf-co.re/docs/usage/configuration#updating-tool-versions) section of the nf-core website.
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