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45 changes: 23 additions & 22 deletions README.md
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</picture>
</h1>

**Multi-steps pipeline dedicated to genetic imputation from simulation to validation**
**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)
Expand All @@ -20,11 +20,11 @@

## Introduction

**nf-core/phaseimpute** is a bioinformatics pipeline to phase and impute genetic data. Different steps are available each corresponding to a dedicated modes.
**nf-core/phaseimpute** is a bioinformatics pipeline to phase and impute genetic data. Different steps are available, each corresponding to a dedicated mode.

### Main steps of the pipeline

The **phaseimpute** pipeline is constituted of 5 main steps:
The **phaseimpute** pipeline consists of 5 main steps:

| Metro map | Modes |
| ---------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
Expand All @@ -45,7 +45,7 @@ sample,file,index
SAMPLE_1X,/path/to/.<bam/cram>,/path/to/.<bai,crai>
```

Each row represents a bam or a cram file with its index file. All input files need to be of the same extension.
Each row represents a BAM or CRAM file along with its index file. All input files need to be of the same extension.
For some tools and steps, you will also need to submit a samplesheet with the reference panel.

A final samplesheet file for the reference panel may look something like the one below. This is for 3 chromosomes.
Expand Down Expand Up @@ -80,18 +80,18 @@ For more details and further functionality, please refer to the [usage documenta
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/).

| steps | Flow chart | Description |
| --------------- | -------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **--panelprep** | <img src="docs/images/metro/PanelPrep.png" alt="Panel preparation" width="600"/> | The preprocessing mode is responsible to the preparation of the multiple input file that will be used by the phasing process. <br> The main processes are : <br> - **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/). <br> - **Normalize** the reference panel to select only the necessary variants. <br> - **Chunking the reference panel** in a subset of region for all the chromosomes. <br> - **Extract** the positions where to perform the imputation. |
| **--impute** | <img src="docs/images/metro/Impute.png" alt="Impute target" width="600"/> | The imputation mode is the core mode of this pipeline. <br> It is constituted of 3 main steps: <br> - **Imputation**: Impute the target dataset on the reference panel using either: <br> &emsp; - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html): It's come with the necessety to compute the genotype likelihoods of the target dataset (done using [BCFTOOLS_mpileup](https://samtools.github.io/bcftools/bcftools.html#mpileup)). <br> &emsp; - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) <br> &emsp; - [**Stitch**](https://github.com/rwdavies/stitch) This steps does not require a reference panel but needs to merge the samples. <br> &emsp; - [**Quilt**](https://github.com/rwdavies/QUILT) <br> - **Ligation**: all the different chunks are merged together then all chromosomes are reunited to output one VCF per sample. |
| **--simulate** | <img src="docs/images/metro/Simulate.png" alt="simulate_metro" width="600"/> | The simulation mode is used to create artificial low informative genetic information from high density data. This allow to compare the imputed result to a _truth_ and therefore evaluate the quality of the imputation. <br> For the moment it is possible to simulate: <br> - Low-pass data by **downsample** BAM or CRAM using [SAMTOOLS_VIEW -s](https://www.htslib.org/doc/samtools-view.html) at different depth. |
| **--validate** | <img src="docs/images/metro/Validate.png" alt="concordance_metro" width="600"/> | This mode compare two vcf together to compute a summary of the differences between them. <br> This step use [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) concordance process. |
| steps | Flow chart | Description |
| ------------------------------------------------------------------- | -------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **--panelprep** | <img src="docs/images/metro/PanelPrep.png" alt="Panel preparation" width="600"/> | The preprocessing mode is responsible for preparing multiple input files that will be used by the phasing and imputation process. <br> The main processes are : <br> - **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/). <br> - **Normalize** the reference panel to select only the necessary variants. <br> - **Chunking the reference panel** into a subset of regions for all the chromosomes. |
| . <br> - **Extract** the positions where to perform the imputation. |
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| **--impute** | <img src="docs/images/metro/Impute.png" alt="Impute target" width="600"/> | The imputation mode is the core mode of this pipeline. <br> It consists of 3 main steps: <br> - **Imputation**: Impute the target dataset on the reference panel using either: <br> &emsp; - [**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)). <br> &emsp; - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) <br> &emsp; - [**Stitch**](https://github.com/rwdavies/stitch) This step does not require a reference panel but needs to merge the samples. <br> &emsp; - [**Quilt**](https://github.com/rwdavies/QUILT) <br> - **Ligation**: all the different chunks are merged together then all chromosomes are reunited to output one VCF per sample. |
| **--simulate** | <img src="docs/images/metro/Simulate.png" alt="simulate_metro" width="600"/> | 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. <br> For the moment it is possible to simulate: <br> - Low-pass data by **downsample** BAM or CRAM using [SAMTOOLS_VIEW -s](https://www.htslib.org/doc/samtools-view.html) at different depth. |
| **--validate** | <img src="docs/images/metro/Validate.png" alt="concordance_metro" width="600"/> | This mode compares two VCF files together to compute a summary of the differences between them. <br> This step uses [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) concordance process. |

## Pipeline output

To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/phaseimpute/results) tab on the nf-core website pipeline page.
For more details about the output files and reports, please refer to the
[output documentation](https://nf-co.re/phaseimpute/output).
For more details on the output files and reports, please refer to the [output documentation](https://nf-co.re/phaseimpute/output).

## Credits

Expand All @@ -112,41 +112,42 @@ For further information or help, don't hesitate to get in touch on the [Slack `#
## Citations

<!-- TODO nf-core: Add citation for pipeline after first release. Uncomment lines below and update Zenodo doi and badge at the top of this file. -->
<!-- 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) -->

<!-- TODO nf-core: Add bibliography of tools and data used in your pipeline -->
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)

You can cite one of the main imputation methods ([`QUILT`](https://github.com/rwdavies/QUILT)) as follows:
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)

You can cite one of the main imputation methods ([`GLIMPSE`](https://github.com/odelaneau/GLIMPSE)) as follows:
[`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:[]()
> _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:[]()
> _Nature genetics_ 2023. doi:[10.1038/s41588-023-01438-3](https://doi.org/10.1038/s41588-023-01438-3)

You can cite one of the main imputation methods ([`STITCH`](https://github.com/rwdavies/STITCH)) as follows:
[`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: []().

An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
> _Nature genetics_ 2016 . doi: [10.1038/ng.3594](https://doi.org/10.1038/ng.3594).

You can cite the `nf-core` publication as follows:

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process {

// TODO nf-core: Check the defaults for all processes
cpus = { 1 * task.attempt }
memory = { 6.GB * task.attempt }
time = { 4.h * task.attempt }
Expand All @@ -24,7 +23,6 @@ process {
// These labels are used and recognised by default in DSL2 files hosted on nf-core/modules.
// If possible, it would be nice to keep the same label naming convention when
// adding in your local modules too.
// TODO nf-core: Customise requirements for specific processes.
// See https://www.nextflow.io/docs/latest/config.html#config-process-selectors
withLabel:process_single {
cpus = { 1 }
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Expand Up @@ -6,8 +6,6 @@ This document describes the output produced by the pipeline. Most of the plots a

The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.

<!-- TODO nf-core: Write this documentation describing your workflow's output -->

## Pipeline overview

## Panel preparation outputs `--steps panelprep`
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## Introduction

<!-- TODO nf-core: Add documentation about anything specific to running your pipeline. For general topics, please point to (and add to) the main nf-core website. -->

## Samplesheet input

You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below.
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Expand Up @@ -212,7 +212,6 @@ profiles {
includeConfig !System.getenv('NXF_OFFLINE') && params.custom_config_base ? "${params.custom_config_base}/nfcore_custom.config" : "/dev/null"

// Load nf-core/phaseimpute custom profiles from different institutions.
// TODO nf-core: Optionally, you can add a pipeline-specific nf-core config at https://github.com/nf-core/configs
// includeConfig !System.getenv('NXF_OFFLINE') && params.custom_config_base ? "${params.custom_config_base}/pipeline/phaseimpute.config" : "/dev/null"

// Set default registry for Apptainer, Docker, Podman, Charliecloud and Singularity independent of -profile
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