From 70e24ec0587b7c37ed3112a1098ee967d9c40c95 Mon Sep 17 00:00:00 2001 From: Louis LE NEZET <58640615+LouisLeNezet@users.noreply.github.com> Date: Wed, 30 Oct 2024 19:06:22 +0100 Subject: [PATCH] Fix URLs and simplify citation (#152) * Update readme * Fix url link * Fix url link in output * Fix url link in output * Fix url link in citation * Add space to badges * Update CHANGELOG * Add white background to images * Update Changelog --- CHANGELOG.md | 1 + CITATIONS.md | 2 +- README.md | 59 +- docs/images/InputSoftware_compatibility.png | Bin 48584 -> 48577 bytes docs/images/metro/Impute.png | Bin 196728 -> 192242 bytes docs/images/metro/MetroMap.png | Bin 1106848 -> 352547 bytes docs/images/metro/MetroMap.svg | 2952 +----------------- docs/images/metro/MetroMap_animated.svg | 2968 +++++++++++++++++++ docs/images/metro/PanelPrep.png | Bin 194134 -> 189956 bytes docs/images/metro/Simulate.png | Bin 101428 -> 103412 bytes docs/images/metro/Validate.png | Bin 97177 -> 95064 bytes docs/images/metro/txt2image.md | 12 +- docs/output.md | 22 +- docs/usage.md | 6 +- 14 files changed, 3003 insertions(+), 3019 deletions(-) create mode 100644 docs/images/metro/MetroMap_animated.svg diff --git a/CHANGELOG.md b/CHANGELOG.md index f8491e5d..042b1474 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -63,6 +63,7 @@ Initial release of nf-core/phaseimpute, created with the [nf-core](https://nf-co - [#144](https://github.com/nf-core/phaseimpute/pull/144) - Documentation updates - [#148](https://github.com/nf-core/phaseimpute/pull/148) - Fix awsfulltest github action for manual dispatch - [#149](https://github.com/nf-core/phaseimpute/pull/149) - Remove the map file from the awsfulltest +- [#152](https://github.com/nf-core/phaseimpute/pull/152) - Fix URLs in the documentation and remove tools citation in the README, use a white background for all images in the documentation. ### `Fixed` diff --git a/CITATIONS.md b/CITATIONS.md index 6cef95ce..ef1d9743 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -26,7 +26,7 @@ > Davies, R. W., Flint, J., Myers, S., & Mott, R.(2016). Rapid genotype imputation from sequence without reference panels. Nature genetics 48, 965–969. -- [Shapeit](https://odelaneau.github.io/shapeit5/) +- [Shapeit](https://doi.org/10.1038/s41588-023-01415-w) > Hofmeister RJ, Ribeiro DM, Rubinacci S., Delaneau O. (2023). Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank. Nature Genetics doi: https://doi.org/10.1038/s41588-023-01415-w diff --git a/README.md b/README.md index 70895708..81b2dcad 100644 --- a/README.md +++ b/README.md @@ -8,23 +8,22 @@ **Multi-step pipeline dedicated to genetic imputation from simulation to validation** [![GitHub Actions CI Status](https://github.com/nf-core/phaseimpute/actions/workflows/ci.yml/badge.svg)](https://github.com/nf-core/phaseimpute/actions/workflows/ci.yml) -[![GitHub Actions Linting Status](https://github.com/nf-core/phaseimpute/actions/workflows/linting.yml/badge.svg)](https://github.com/nf-core/phaseimpute/actions/workflows/linting.yml)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/phaseimpute/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) -[![nf-test](https://img.shields.io/badge/unit_tests-nf--test-337ab7.svg)](https://www.nf-test.com) +[![GitHub Actions Linting Status](https://github.com/nf-core/phaseimpute/actions/workflows/linting.yml/badge.svg)](https://github.com/nf-core/phaseimpute/actions/workflows/linting.yml) [![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/phaseimpute/results) [![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) [![nf-test](https://img.shields.io/badge/unit_tests-nf--test-337ab7.svg)](https://www.nf-test.com) [![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A524.04.2-23aa62.svg)](https://www.nextflow.io/) [![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/) [![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/) [![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/) [![Launch on Seqera Platform](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Seqera%20Platform-%234256e7)](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/phaseimpute) -[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23phaseimpute-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/phaseimpute)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core) +[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23phaseimpute-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/phaseimpute) [![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core) [![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core) [![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core) ## Introduction **nf-core/phaseimpute** is a bioinformatics pipeline to phase and impute genetic data. The pipeline is constituted of five main steps: -| Metro map | Modes | -| ---------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| metromap | - **Check chromosomes names**: Validates the presence of the different contigs in all variants and alignment files, ensuring data compatibility for further processing
- **Panel preparation**: Perfoms the phasing, QC, variant filtering, variant annotation of the reference panel
- **Imputation**: Imputes genotypes in the target dataset using the reference panel
- **Simulate**: Generates simulated datasets from high-quality target data for testing and validation purposes.
- **Concordance**: Evaluates the accuracy of imputation by comparing the imputed data against a truth dataset. | +| Metro map | Modes | +| ------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| metromap | - **Check chromosomes names**: Validates the presence of the different contigs in all variants and alignment files, ensuring data compatibility for further processing
- **Panel preparation**: Perfoms the phasing, QC, variant filtering, variant annotation of the reference panel
- **Imputation**: Imputes genotypes in the target dataset using the reference panel
- **Simulate**: Generates simulated datasets from high-quality target data for testing and validation purposes.
- **Concordance**: Evaluates the accuracy of imputation by comparing the imputed data against a truth dataset. | ## Usage @@ -74,14 +73,14 @@ For more details and further functionality, please refer to the [usage documenta ## Description of the different steps of the pipeline Here is a short description of the different steps of the pipeline. -For more information please refer to the [documentation](https://nf-core.github.io/phaseimpute/usage/). +For more information please refer to the [usage documentation](https://nf-co.re/phaseimpute/usage). -| steps | Flow chart | Description | -| --------------- | -------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| **--panelprep** | Panel preparation | The preprocessing mode is responsible for preparing multiple input files that will be used by the phasing and imputation process.
The main processes are :
- **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/).
- **Normalize** the reference panel to select only the necessary variants.
- **Chunking the reference panel** into a subset of regions for all the chromosomes.
- **Extract** the positions where to perform the imputation. | -| **--impute** | Impute target | The imputation mode is the core mode of this pipeline.
It consists of 3 main steps:
- **Imputation**: Impute the target dataset on the reference panel using either:
  - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html): It comes with the necessity to compute the genotype likelihoods of the target dataset (done using [BCFTOOLS_mpileup](https://samtools.github.io/bcftools/bcftools.html#mpileup)).
  - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html)
  - [**Stitch**](https://github.com/rwdavies/stitch) This step does not require a reference panel but needs to merge the samples.
  - [**Quilt**](https://github.com/rwdavies/QUILT)
- **Ligation**: all the different chunks are merged together then all chromosomes are reunited to output one VCF per sample. | -| **--simulate** | simulate_metro | The simulation mode is used to create artificial low informative genetic information from high density data. This allows the comparison of the imputed result to a _truth_ and therefore evaluates the quality of the imputation.
For the moment it is possible to simulate:
- Low-pass data by **downsample** BAM or CRAM using [SAMTOOLS_VIEW -s](https://www.htslib.org/doc/samtools-view.html) at different depth. | -| **--validate** | concordance_metro | This mode compares two VCF files together to compute a summary of the differences between them.
This step uses [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) concordance process. | +| steps | Flow chart | Description | +| --------------- | -------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **--panelprep** | Panel preparation | The preprocessing mode is responsible for preparing multiple input files that will be used by the phasing and imputation process.
The main processes are :
- **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/).
- **Normalize** the reference panel to select only the necessary variants.
- **Chunking the reference panel** into a subset of regions for all the chromosomes.
- **Extract** the positions where to perform the imputation. | +| **--impute** | Impute target | The imputation mode is the core mode of this pipeline.
It consists of 3 main steps:
- **Imputation**: Impute the target dataset on the reference panel using either:
  - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html): It comes with the necessity to compute the genotype likelihoods of the target dataset (done using [`bcftools mpileup`](https://samtools.github.io/bcftools/bcftools.html#mpileup)).
  - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/)
  - [**Stitch**](https://github.com/rwdavies/stitch) This step does not require a reference panel but needs to merge the samples.
  - [**Quilt**](https://github.com/rwdavies/QUILT)
- **Ligation**: all the different chunks are merged together then all chromosomes are reunited to output one VCF per sample. | +| **--simulate** | simulate_metro | The simulation mode is used to create artificial low informative genetic information from high density data. This allows the comparison of the imputed result to a _truth_ and therefore evaluates the quality of the imputation.
For the moment it is possible to simulate:
- Low-pass data by **downsample** BAM or CRAM using [`samtools view -s`](https://www.htslib.org/doc/samtools-view.html) at different depth. | +| **--validate** | concordance_metro | This mode compares two VCF files together to compute a summary of the differences between them.
This step uses [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/) concordance process. | ## Pipeline output @@ -111,39 +110,7 @@ For further information or help, don't hesitate to get in touch on the [Slack `# If you use nf-core/phaseimpute for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) -An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file. - -You can cite the main imputation methods as follows: - -[`QUILT`](https://github.com/rwdavies/QUILT): - -> **Rapid genotype imputation from sequence with reference panels.** -> -> Davies, R. W., Kucka, M., Su, D., Shi, S., Flanagan, M., Cunniff, C. M., Chan, Y. F., & Myers, S. -> -> _Nature genetics_ 2021 June 03. doi: [10.1038/s41588-021-00877-0](https://doi.org/10.1038/s41588-021-00877-0) - -[`GLIMPSE`](https://github.com/odelaneau/GLIMPSE): - -> **Efficient phasing and imputation of low-coverage sequencing data using large reference panels.** -> -> Rubinacci, S., Ribeiro, D. M., Hofmeister, R. J., & Delaneau, O. -> -> _Nature genetics_ 2021. doi:[10.1038/s41588-020-00756-0](https://doi.org/10.1038/s41588-020-00756-0) - -> **Imputation of low-coverage sequencing data from 150,119 UK Biobank genomes** -> -> Rubinacci, S., Hofmeister, R. J., Sousa da Mota, B., & Delaneau, O. -> -> _Nature genetics_ 2023. doi:[10.1038/s41588-023-01438-3](https://doi.org/10.1038/s41588-023-01438-3) - -[`STITCH`](https://github.com/rwdavies/STITCH): - -> **Rapid genotype imputation from sequence without reference panels.** -> -> Davies, R. W., Flint, J., Myers, S., & Mott, R. -> -> _Nature genetics_ 2016 . doi: [10.1038/ng.3594](https://doi.org/10.1038/ng.3594). +An extensive list of references for the tools used by the pipeline, including QUILT, GLIMPSE, and STITCH, can be found in the [`CITATIONS.md`](CITATIONS.md) file. 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b/docs/images/metro/txt2image.md index dbc467fd..95d6b2ce 100644 --- a/docs/images/metro/txt2image.md +++ b/docs/images/metro/txt2image.md @@ -12,10 +12,10 @@ To use drawio ```bash drawio --version -drawio docs/images/metro/MetroMap.xml --export --format png --page-index 2 --layers 1 --output docs/images/metro/MetroMap.png --scale 3 --transparent -drawio docs/images/metro/MetroMap.xml --export --format svg --page-index 2 --layers 2,3,4,5 --output docs/images/metro/MetroMap.svg --transparent -drawio docs/images/metro/MetroMap.xml --export --format png --page-index 3 --layers 1 --output docs/images/metro/Simulate.png --scale 3 --transparent -drawio docs/images/metro/MetroMap.xml --export --format png --page-index 4 --layers 0 --output docs/images/metro/PanelPrep.png --scale 3 --transparent -drawio docs/images/metro/MetroMap.xml --export --format png --page-index 5 --layers 1 --output docs/images/metro/Impute.png --scale 3 --transparent -drawio docs/images/metro/MetroMap.xml --export --format png --page-index 6 --layers 0 --output docs/images/metro/Validate.png --scale 3 --transparent +drawio docs/images/metro/MetroMap.xml --export --format png --page-index 2 --layers 1 --output docs/images/metro/MetroMap.png --scale 3 +drawio docs/images/metro/MetroMap.xml --export --format svg --page-index 2 --layers 2,3,4,5 --output docs/images/metro/MetroMap.svg +drawio docs/images/metro/MetroMap.xml --export --format png --page-index 3 --layers 1 --output docs/images/metro/Simulate.png --scale 3 +drawio docs/images/metro/MetroMap.xml --export --format png --page-index 4 --layers 0 --output docs/images/metro/PanelPrep.png --scale 3 +drawio docs/images/metro/MetroMap.xml --export --format png --page-index 5 --layers 1 --output docs/images/metro/Impute.png --scale 3 +drawio docs/images/metro/MetroMap.xml --export --format png --page-index 6 --layers 0 --output docs/images/metro/Validate.png --scale 3 ``` diff --git a/docs/output.md b/docs/output.md index a759cfcd..2c312fa5 100644 --- a/docs/output.md +++ b/docs/output.md @@ -12,12 +12,11 @@ The directories listed below will be created in the results directory after the This steps of the pipeline performs a QC of the reference panel data and produces the necessary files for imputation (`--steps impute`). It has two optional modes: reference panel phasing with SHAPEIT5 and removal of specified samples from reference panel. -- [Remove Multiallelics](#multiallelics) - Remove multiallelic sites from the reference panel -- [Convert](#convert) - Convert reference panel to .hap and .legend files -- [Posfile](#posfile) - Produce a TSV with the list of positions to genotype (for STITCH/QUILT) -- [Sites](#sites) - Produce a TSV with the list of positions to genotype (for GLIMPSE1) -- [Glimpse Chunk](#glimpse) - Create chunks of the reference panel -- [CSV](#csv) - Obtain a CSV from this step +- [Normalize reference panel](#panel-directory) - Remove multiallelic sites from the reference panel and compute allele frequencies if needed +- [Convert](#haplegend-directory) - Convert reference panel to .hap and .legend files +- [Posfile](#sites-directory) - Produce a TSV with the list of positions to genotype for the different tools +- [Chromosomes chunks](#chunks-directory) - Create chunks of the reference panel +- [CSV](#csv-directory) - Obtain a CSV from this step The directory structure from `--steps panelprep` is: @@ -55,7 +54,7 @@ A directory containing the reference panel per chromosome after preprocessing. T -[bcftools](https://samtools.github.io/bcftools/bcftools.html) aids in the conversion of vcf files to .hap and .legend files. A .samples file is also generated. Once that you have generated the hap and legend files for your reference panel, you can skip the reference preparation steps and directly submit these files for imputation. The hap and legend files are input files used with `--tools quilt`. +[`bcftools convert`](https://samtools.github.io/bcftools/bcftools.html#convert) aids in the conversion of vcf files to .hap and .legend files. A .samples file is also generated. Once that you have generated the hap and legend files for your reference panel, you can skip the reference preparation steps and directly submit these files for imputation. The hap and legend files are input files used with `--tools quilt`. ### Sites directory @@ -72,9 +71,9 @@ A directory containing the reference panel per chromosome after preprocessing. T -[bcftools query](https://samtools.github.io/bcftools/bcftools.html) produces VCF (`*.vcf.gz`) files per chromosome. These QCed VCFs can be gathered into a csv and used with all the tools in `--steps impute` using the flag `--panel`. +[`bcftools query`](https://samtools.github.io/bcftools/bcftools.html#query) produces VCF (`*.vcf.gz`) files per chromosome. These QCed VCFs can be gathered into a csv and used with all the tools in `--steps impute` using the flag `--panel`. -In addition, [bcftools query](https://samtools.github.io/bcftools/bcftools.html) produces tab-delimited files (`*_tsv.txt`) and, together with the VCFs, they can be gathered into a samplesheet and directly submitted for imputation with `--tools glimpse1,stitch` and `--posfile`. +In addition, [bcftools query](https://samtools.github.io/bcftools/bcftools.html#query) produces tab-delimited files (`*_tsv.txt`) and, together with the VCFs, they can be gathered into a samplesheet and directly submitted for imputation with `--tools glimpse1,stitch` and `--posfile`. ### Chunks directory @@ -86,7 +85,7 @@ In addition, [bcftools query](https://samtools.github.io/bcftools/bcftools.html) -[Glimpse1 chunk](https://odelaneau.github.io/GLIMPSE/) defines chunks where to run imputation. For further reading and documentation see the [Glimpse1 documentation](https://odelaneau.github.io/GLIMPSE/glimpse1/commands.html). Once that you have generated the chunks for your reference panel, you can skip the reference preparation steps and directly submit this file for imputation. +[Glimpse1 chunk](https://odelaneau.github.io/GLIMPSE/glimpse1/) defines chunks where to run imputation. For further reading and documentation see the [Glimpse1 documentation](https://odelaneau.github.io/GLIMPSE/glimpse1/commands.html). Once that you have generated the chunks for your reference panel, you can skip the reference preparation steps and directly submit this file for imputation. ### CSV directory @@ -117,13 +116,12 @@ The results from steps impute will have the following directory structure: -[bcftools concat](https://samtools.github.io/bcftools/bcftools.html) will produce a single VCF from a list of imputed VCFs in chunks. +[`bcftools concat`](https://samtools.github.io/bcftools/bcftools.html#concat) will produce a single VCF from a list of imputed VCFs in chunks. ## Reports Reports contain useful metrics and pipeline information for the different modes. -- [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution diff --git a/docs/usage.md b/docs/usage.md index 9c49e18c..0b756876 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -95,7 +95,7 @@ panel,chr,vcf,index,hap,legend | `hap` | Full path to ".hap.gz" compressed file containing the reference panel haplotypes in ["haps" format](https://www.cog-genomics.org/plink/2.0/formats#haps). (Required by QUILT) | | `legend` | Full path to ".legend.gz" compressed file containing the reference panel sites in ["legend" format](https://www.cog-genomics.org/plink/2.0/formats#legend). (Required by QUILT, GLIMPSE1 and STITCH) | -The `legend` file should be a TSV with the following structure, similar to that from [BCFTOOLS convert documentation](https://samtools.github.io/bcftools/bcftools.html#convert) with the `--haplegendsample` command : File is space separated with a header ("id,position,a0,a1"), one row per SNP, with the following columns: +The `legend` file should be a TSV with the following structure, similar to that from [`bcftools convert` documentation](https://samtools.github.io/bcftools/bcftools.html#convert) with the `--haplegendsample` command : File is space separated with a header ("id,position,a0,a1"), one row per SNP, with the following columns: - Column 1: chromosome:position_ref allele_alternate allele - Column 2: physical position (sorted from smallest to largest) @@ -496,10 +496,8 @@ nextflow pull nf-core/phaseimpute ### Reproducibility -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. 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. -First, go to the [nf-core/phaseimpute releases page](https://github.com/nf-core/phaseimpute/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. First, go to the [nf-core/phaseimpute releases page](https://github.com/nf-core/phaseimpute/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. 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. For example, at the bottom of the MultiQC reports. @@ -520,7 +518,6 @@ These options are part of Nextflow and use a _single_ hyphen (pipeline parameter Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments. -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. 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. :::info @@ -556,7 +553,6 @@ If `-profile` is not specified, the pipeline will run locally and expect all sof ### `-resume` -Specify this when restarting a pipeline. Nextflow will use cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously. For input to be considered the same, not only the names must be identical but the files' contents as well. For more info about this parameter, see [this blog post](https://www.nextflow.io/blog/2019/demystifying-nextflow-resume.html). Specify this when restarting a pipeline. Nextflow will use cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously. For input to be considered the same, not only the names must be identical but the files' contents as well. For more info about this parameter, see [this blog post](https://www.nextflow.io/blog/2019/demystifying-nextflow-resume.html). You can also supply a run name to resume a specific run: `-resume [run-name]`. Use the `nextflow log` command to show previous run names.

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