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.gitignore

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		nextflow
		.nextflow.log*
		.nextflow/
		work/
		results
		workspace.code-workspace

.gitmodules

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		[submodule "src/sge_modules"]
		path = src/.psmn_modules
		url = gitlab_lbmc:PSMN/modules.git
		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		[submodule "src/.docker_modules/hicstuff/3.1.3/hicstuff"]
		path = src/.docker_modules/hicstuff/3.1.3/hicstuff
		url = git@github.com:koszullab/hicstuff.git

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		Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
		Upstream-Name: nextflow
		Upstream-Contact: Laurent Modolo <laurent.modolo@ens-lyon.fr>
		Source: https://gitbio.ens-lyon.fr/LBMC/nextflow

		# Sample paragraph, commented out:
		#
		# Files: src/*
		# Copyright: $YEAR $NAME <$CONTACT>
		# License: ...

CHANGELOG.md

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		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		# Changelog
		All notable changes to this project will be documented in this file.

		The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
		and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

		## [0.4.0] - 2019-11-18
		### Added
		- Add new tools (star,...)
		- conda support at the psmn

		## Changed
		- configuration simplification
		- docker and singularity image download instead of local build
		- hidden directories in `src` for project clarity (only `nf_modules` is visible)

		## Removed
		- conda support at in2p3 with `-profile in2p3_conda`

		## [0.3.0] - 2019-05-23
		### Added
		- Add new tools (umi_tools, fastp,...)

CONTRIBUTING.md

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		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		# Contributing

		When contributing to this repository, please first discuss the change you wish to make via issue,
		email, or any other method with the owners of this repository before making a change.
		When contributing to this repository, please first discuss the change you wish to make via issues,
		email, or on the [ENS-Bioinfo channel](https://matrix.to/#/#ens-bioinfo:matrix.org) before making a change.

		## Forking

		In git, the [action of forking](https://git-scm.com/book/en/v2/GitHub-Contributing-to-a-Project) means that you are going to make your own private copy of a repository. You can then write modifications in your project, and if they are of interest for the source repository create a merge request (here [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow)). Merge requests are sent to the source repository to ask the maintainers to integrate modifications.

		![merge request button](./doc/img/merge_request.png)

		## Project organization

		The `LBMC/nextflow` project is structured as follows:
		- all the code is in the `src/` folder
		- scripts downloading external tools should download them in the `bin/` folder
		- all the documentation (including this file) can be found int he `doc/` folder
		- the `data` and `results` folders contain the data and results of your pipelines and are ignored by `git`

		## Code structure

		The `src/` folder is where we want to save the pipeline (`.nf`) scripts. This folder also contains
		- the `src/install_nextflow.sh` to install the nextflow executable at the root of the project.
		- some pipelines examples (like the one build during the nf_pratical)
		- the `src/nextflow.config` global configuration file which contains the `docker`, `singularity`, `psmn` and `ccin2p3` profiles.
		- the `src/nf_modules` folder contains per tools `main.nf` modules with predefined process that users can import in their projects with the [DSL2](https://www.nextflow.io/docs/latest/dsl2.html)

		But also some hidden folders that users don't need to see when building their pipeline:
		- the `src/.docker_modules` contains the recipes for the `docker` containers used in the `src/nf_modules/<tool_names>/main.nf` files
		- the `src/.singularity_in2p3` and `src/.singularity_psmn` are symbolic links to the shared folder where the singularity images are downloaded on the PSMN and CCIN2P3

		# Proposing a new tool

		Each tool named `<tool_name>` must have two dedicated folders:

		- [`src/nf_modules/<tool_name>`](./src/nf_modules/fastp/) where users can find `.nf` files to include
		- [`src/.docker_modules/<tool_name>/<version_number>`](./src/.docker_modules/fastp/0.20.1/) where we have the [`Dockerfile`](./src/.docker_modules/fastp/0.20.1/Dockerfile) to construct the container used in the `main.nf` file

		## `src/nf_module` guide lines

		We are going to take the [`fastp`, `nf_module`](./src/nf_modules/fastp/) as an example.

		The [`src/nf_modules/<tool_name>`](./src/nf_modules/fastp/) should contain a [`main.nf`](./src/nf_modules/fastp/main.nf) file that describe at least one process using `<tool_name>`

		### container informations

		The first two lines of [`main.nf`](./src/nf_modules/fastp/main.nf) should define two variables
		```Groovy
		version = "0.20.1"
		container_url = "lbmc/fastp:${version}"
		```

		we can then use the `container_url` definition in each `process` in the `container` attribute.
		In addition to the `container` directive, each `process` should have one of the following `label` attributes (defined in the `src/nextflow.config` file)
		- `big_mem_mono_cpus`
		- `big_mem_multi_cpus`
		- `small_mem_mono_cpus`
		- `small_mem_multi_cpus`

		```Groovy
		process fastp {
		container = "${container_url}"
		label = "big_mem_multi_cpus"
		...
		}
		```

		### process options

		Before each process, you should declare at least two `params.` variables:
		- A `params.<process_name>` defaulting to `""` (empty string) to allow user to add more command line option to your process without rewriting the process definition
		- A `params.<process_name>_out` defaulting to `""` (empty string) that define the `results/` subfolder where the process output should be copied if the user wants to save the process output

		```Groovy
		params.fastp = ""
		params.fastp_out = ""
		process fastp {
		container = "${container_url}"
		label "big_mem_multi_cpus"
		if (params.fastp_out != "") {
		publishDir "results/${params.fastp_out}", mode: 'copy'
		}
		...
		script:
		"""
		fastp --thread ${task.cpus} \
		${params.fastp} \
		...
		"""
		}
		```

		The user can then change the value of these variables:
		- from the command line `--fastp "--trim_head1=10"``
		- with the `include` command within their pipeline: `include { fastq } from "nf_modules/fastq/main" addParams(fastq_out: "QC/fastq/")
		- by defining the variable within their pipeline: `params.fastq_out = "QC/fastq/"

		### `input` and `output` format

		You should always use `tuple` for input and output channel format with at least:
		- a `val` containing variable(s) related to the item
		- a `path` for the file(s) that you want to process

		for example:

		```Groovy
		process fastp {
		container = "${container_url}"
		label "big_mem_multi_cpus"
		tag "$file_id"
		if (params.fastp_out != "") {
		publishDir "results/${params.fastp_out}", mode: 'copy'
		}

		input:
		tuple val(file_id), path(reads)

		output:
		tuple val(file_id), path("*.fastq.gz"), emit: fastq
		tuple val(file_id), path("*.html"), emit: html
		tuple val(file_id), path("*.json"), emit: report
		...
		```

		Here `file_id` can be anything from a simple identifier to a list of several variables.
		In which case the first item of the List should be usable as a file prefix.
		So you have to keep that in mind if you want to use it to define output file names (you can test for that with `file_id instanceof List`).
		In some case, the `file_id` may be a Map to have a cleaner access to the `file_id` content by explicit keywords.

		If you want to use information within the `file_id` to name outputs in your `script` section, you can use the following snipet:

		```Groovy
		script:
		switch(file_id) {
		case {it instanceof List}:
		file_prefix = file_id[0]
		break
		case {it instanceof Map}:
		file_prefix = file_id.values()[0]
		break
		default:
		file_prefix = file_id
		break
		}
		```

		and use the `file_prefix` variable.

		This also means that channel emitting `path` item should be transformed with at least the following map function:

		```Groovy
		.map { it -> [it.simpleName, it]}
		```

		for example

		```Groovy
		channel
		.fromPath( params.fasta )
		.ifEmpty { error "Cannot find any fasta files matching: ${params.fasta}" }
		.map { it -> [it.simpleName, it]}
		.set { fasta_files }
		```


		The rationale behind taking a `file_id` and emitting the same `file_id` is to facilitate complex channel operations in pipelines without having to rewrite the `process` blocks.

		### dealing with paired-end and single-end data

		When oppening fastq files with `channel.fromFilePairs( params.fastq )`, item in the channel have the following shape:

		```Groovy
		[file_id, [read_1_file, read_2_file]]
		```

		To make this call more generic, we can use the `size: -1` option, and accept arbitrary number of associated fastq files:

		```Groovy
		channel.fromFilePairs( params.fastq, size: -1 )
		```

		Please note we have a code of conduct, please follow it in all your interactions with the project.
		will thus give `[file_id, [read_1_file, read_2_file]]` for paired-end data and `[file_id, [read_1_file]]` for single-end data

		## Pull Request Process

		1. Ensure any install or build dependencies are removed before the end of the layer when doing a
		build.
		2. Update the README.md with details of changes to the interface, this includes new environment
		variables, exposed ports, useful file locations and container parameters.
		3. Increase the version numbers in any examples files and the README.md to the new version that this
		Pull Request would represent. The versioning scheme we use is [SemVer](http://semver.org/).
		4. You may merge the Pull Request in once you have the sign-off of two other developers, or if you
		do not have permission to do that, you may request the second reviewer to merge it for you.
		You can the use tests on `read.size()` to define conditional `script` block:

		## Code of Conduct
		```Groovy
		...
		script:
		if (file_id instanceof List){
		file_prefix = file_id[0]
		} else {
		file_prefix = file_id
		}
		if (reads.size() == 2)
		"""
		fastp --thread ${task.cpus} \
		${params.fastp} \
		--in1 ${reads[0]} \
		--in2 ${reads[1]} \
		--out1 ${file_prefix}_R1_trim.fastq.gz \
		--out2 ${file_prefix}_R2_trim.fastq.gz \
		--html ${file_prefix}.html \
		--json ${file_prefix}_fastp.json \
		--report_title ${file_prefix}
		"""
		else
		"""
		fastp --thread ${task.cpus} \
		${params.fastp} \
		--in1 ${reads[0]} \
		--out1 ${file_prefix}_trim.fastq.gz \
		--html ${file_prefix}.html \
		--json ${file_prefix}_fastp.json \
		--report_title ${file_prefix}
		"""
		...
		```

		### Our Pledge
		### Complex processes

		In the interest of fostering an open and welcoming environment, we as
		contributors and maintainers pledge to making participation in our project and
		our community a harassment-free experience for everyone, regardless of age, body
		size, disability, ethnicity, gender identity and expression, level of experience,
		nationality, personal appearance, race, religion, or sexual identity and
		orientation.
		Sometime you want to do write complex processes, for example for `fastp` we want to have predefine `fastp` process for different protocols, order of adapter trimming and reads clipping.
		We can then use the fact that `process` or named `workflow` can be interchangeably imported with th [DSL2](https://www.nextflow.io/docs/latest/dsl2.html#workflow-composition).

		### Our Standards
		With the following example, the user can simply include the `fastp` step without knowing that it's a named `workflow` instead of a `process`.
		By specifying the `params.fastp_protocol`, the `fastp` step will transparently switch betwen the different `fastp` `process`es.
		Here `fastp_default` or `fastp_accel_1splus`, and other protocols can be added later, pipeline will be able to handle these new protocols by simply updating from the `upstream` repository without changing their codes.

		Examples of behavior that contributes to creating a positive environment
		include:
		```Groovy
		params.fastp_protocol = ""
		workflow fastp {
		take:
		fastq

		* Using welcoming and inclusive language
		* Being respectful of differing viewpoints and experiences
		* Gracefully accepting constructive criticism
		* Focusing on what is best for the community
		* Showing empathy towards other community members
		main:
		switch(params.fastp_protocol) {
		case "accel_1splus":
		fastp_accel_1splus(fastq)
		fastp_accel_1splus.out.fastq.set{res_fastq}
		fastp_accel_1splus.out.report.set{res_report}
		break;
		default:
		fastp_default(fastq)
		fastp_default.out.fastq.set{res_fastq}
		fastp_default.out.report.set{res_report}
		break;
		}
		emit:
		fastq = res_fastq
		report = res_report
		}
		```

		Examples of unacceptable behavior by participants include:
		## `src/.docker_modules` guide lines

		* The use of sexualized language or imagery and unwelcome sexual attention or
		advances
		* Trolling, insulting/derogatory comments, and personal or political attacks
		* Public or private harassment
		* Publishing others' private information, such as a physical or electronic
		address, without explicit permission
		* Other conduct which could reasonably be considered inappropriate in a
		professional setting
		We are going to take the [`fastp`, `.docker_modules`](./src/.docker_module/fastp/0.20.1/) as an example.

		### Our Responsibilities
		The [`src/.docker_modules/<tool_name>/<version_number>`](./src/nf_modules/fastp/0.20.1/) should contain a [`Dockerfile`](./src/.docker_module/fastp/0.20.1/Dockerfile) and a [`docker_init.sh`](./src/.docker_module/fastp/0.20.1/docker_init.sh).

		Project maintainers are responsible for clarifying the standards of acceptable
		behavior and are expected to take appropriate and fair corrective action in
		response to any instances of unacceptable behavior.
		### `Dockerfile`

		Project maintainers have the right and responsibility to remove, edit, or
		reject comments, commits, code, wiki edits, issues, and other contributions
		that are not aligned to this Code of Conduct, or to ban temporarily or
		permanently any contributor for other behaviors that they deem inappropriate,
		threatening, offensive, or harmful.
		The [`Dockerfile`](./src/.docker_module/fastp/0.20.1/Dockerfile) shoud contains a `docker` recipe to build a image with `<tool_name>` installed in a system-wide binary folder (`/bin`, `/usr/local/bin/`, etc).
		Therefore, your scripts are easily accessible from within the container.

		### Scope
		This recipe should have:

		This Code of Conduct applies both within project spaces and in public spaces
		when an individual is representing the project or its community. Examples of
		representing a project or community include using an official project e-mail
		address, posting via an official social media account, or acting as an appointed
		representative at an online or offline event. Representation of a project may be
		further defined and clarified by project maintainers.
		- an easily changeable `<version_number>` to be able to update the corresponding image to a newer version of the tool
		- the `ps` executable (package `procps` in debian)
		- a default `bash` command (`CMD ["bash"]`)

		### Enforcement
		### `docker_init.sh`

		Instances of abusive, harassing, or otherwise unacceptable behavior may be
		reported by contacting the project team at [INSERT EMAIL ADDRESS]. All
		complaints will be reviewed and investigated and will result in a response that
		is deemed necessary and appropriate to the circumstances. The project team is
		obligated to maintain confidentiality with regard to the reporter of an incident.
		Further details of specific enforcement policies may be posted separately.
		The [`docker_init.sh`](./src/.docker_module/fastp/0.20.1/docker_init.sh) script is a small sh script with the following content:

		Project maintainers who do not follow or enforce the Code of Conduct in good
		faith may face temporary or permanent repercussions as determined by other
		members of the project's leadership.
		```sh
		#!/bin/sh
		docker pull lbmc/fastp:0.20.1
		docker build src/.docker_modules/fastp/0.20.1 -t 'lbmc/fastp:0.20.1'
		docker push lbmc/fastp:0.20.1
		```

		### Attribution
		We want to be able to execute the `src/.docker_module/fastp/0.20.1/docker_init.sh` from the root of the project to :

		This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
		available at [http://contributor-covenant.org/version/1/4][version]
		- try to download the corresponding container if it exists on the [Docker Hub](https://hub.docker.com/repository/docker/lbmc/)
		- if not build the container from the correspondig [`Dockerfile`](./src/.docker_module/fastp/0.20.1/Dockerfile) and with the same name as the name we would get from the `docker pull` command
		- push the container on the [Docker Hub](https://hub.docker.com/repository/docker/lbmc/) (only [laurent.modolo@ens-lyon.fr](mailto:laurent.modolo@ens-lyon.fr) can do this step for the group lbmc)

		[homepage]: http://contributor-covenant.org
		[version]: http://contributor-covenant.org/version/1/4/

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README.md

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		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		# nextflow pipeline

		This repository is a template and a library repository to help you build nextflow pipeline.
		You can fork this repository to build your own pipeline.

		## Getting the last updates

		To get the last commits from this repository into your fork use the following commands:

		For the first time:
		```sh
		git remote add upstream git@gitbio.ens-lyon.fr:LBMC/nextflow.git
		git pull upstream master
		```

		Then to make an update:
		```sh
		git remote add upstream gitlab_lbmc:pipelines/nextflow.git
		git pull upstream master
		git merge upstream/master
		```
		If you created your `.config` file before version `0.4.0` you need to run the script `src/.update_config.sh` to use the latest docker, singularity and conda configuration (don't forget to check your config files afterward for typos).

		## Getting Started

		These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
		These instructions will get you a copy of the project as a template when you want to build your own pipeline.

		[you can follow them here.](doc/getting_started.md)

		## Available tools
		## Building your pipeline

		[The list of available tools.](doc/available_tools.md)
		You can follow the [building your pipeline guide](./doc/building_your_pipeline.md) for a gentle introduction to `nextflow` and taking advantage of this template to build your pipelines.

		## Projects using nextflow
		## Existing Nextflow pipeline

		[A list of projects using nextflow at the LBMC.](doc/nf_projects.md)
		Before starting a new project, you can check if someone else didn’t already to the work !
		- [on the nextflow project page](./doc/nf_projects.md)
		- [on the nf-core project](https://nf-co.re/pipelines)

		## Contributing

		Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.

		## Versioning

		We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/tags).
		If you want to add more tools to this project, please read the [CONTRIBUTING.md](CONTRIBUTING.md).

		## Authors

		* Laurent Modolo - Initial work

		See also the list of [contributors](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/graphs/master) who participated in this project.
		See also the list of [contributors](https://gitbio.ens-lyon.fr/pipelines/nextflow/graphs/master) who participated in this project.

		## License

bin/.gitignore

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		*

data/.gitignore

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		*

doc/.gitignore

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		*.pdf

doc/Makefile

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		all: TP_experimental_biologists.pdf TP_computational_biologists.pdf ../public/TP_experimental_biologists.html ../public/TP_computational_biologists.html

		../public/TP_experimental_biologists.html: TP_experimental_biologists.md
		pandoc -s TP_experimental_biologists.md -o ../public/TP_experimental_biologists.html

		../public/TP_computational_biologists.html: TP_computational_biologists.md
		pandoc -s TP_computational_biologists.md -o ../public/TP_computational_biologists.html

		TP_experimental_biologists.pdf: TP_experimental_biologists.md
		R -e 'require(rmarkdown); rmarkdown::render("TP_experimental_biologists.md")'

		TP_computational_biologists.pdf: TP_computational_biologists.md
		R -e 'require(rmarkdown); rmarkdown::render("TP_computational_biologists.md")'

doc/TP_computational_biologists.md

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		---
		title: "TP for computational biologists"
		author: Laurent Modolo [laurent.modolo@ens-lyon.fr](mailto:laurent.modolo@ens-lyon.fr)
		date: 20 Jun 2018
		output:
		pdf_document:
		toc: true
		toc_depth: 3
		number_sections: true
		highlight: tango
		latex_engine: xelatex
		---

		The goal of this practical is to learn how to wrap tools in [Docker](https://www.docker.com/what-docker) or [Environment Module](http://www.ens-lyon.fr/PSMN/doku.php?id=documentation:tools:modules) to make them available to nextflow on a personal computer or at the [PSMN](http://www.ens-lyon.fr/PSMN/doku.php).

		Here we assume that you followed the [TP for experimental biologists](./TP_experimental_biologists.md), and that you know the basics of [Docker containers](https://www.docker.com/what-container) and [Environment Module](http://www.ens-lyon.fr/PSMN/doku.php?id=documentation:tools:modules). We are also going to assume that you know how to build and use a nextflow pipeline from the template [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow).

		For the practical you can either work with the WebIDE of Gitlab, or locally as described in the [git: basis formation](https://gitlab.biologie.ens-lyon.fr/formations/git_basis).

		# Docker

		To run a tool within a [Docker container](https://www.docker.com/what-container) you need to write a `Dockerfile`.

		[`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile) are found in the [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow) project under `src/docker_modules/`. Each [`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile) is paired with a [`docker_init.sh`](./src/docker_modules/kallisto/0.44.0/docker_init.sh) file like following the example for `Kallisto` version `0.43.1`:

		```sh
		$ ls -l src/docker_modules/kallisto/0.43.1/
		total 16K
		drwxr-xr-x 2 laurent users 4.0K Jun 5 19:06 ./
		drwxr-xr-x 3 laurent users 4.0K Jun 6 09:49 ../
		-rw-r--r-- 1 laurent users 587 Jun 5 19:06 Dockerfile
		-rwxr-xr-x 1 laurent users 79 Jun 5 19:06 docker_init.sh*
		```

		## [`docker_init.sh`](./src/docker_modules/kallisto/0.44.0/docker_init.sh)
		The [`docker_init.sh`](./src/docker_modules/kallisto/0.44.0/docker_init.sh) is a simple sh script with executable rights (`chmod +x`). By executing this script, the user creates a [Docker container](https://www.docker.com/what-container) with the tool installed a specific version. You can check the [`docker_init.sh`](./src/docker_modules/kallisto/0.44.0/docker_init.sh) file of any implemented tools as a template.

		Remember that the name of the [container](https://www.docker.com/what-container) must be in lower case and in the format `<tool_name>:<version>`.
		For tools without a version number you can use a commit hash instead.

		## [`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile)

		The recipe to wrap your tool in a [Docker container](https://www.docker.com/what-container) is written in a [`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile) file.

		For `Kallisto` version `0.44.0` the header of the `Dockerfile` is :

		```Docker
		FROM ubuntu:18.04
		MAINTAINER Laurent Modolo

		ENV KALLISTO_VERSION=0.44.0
		```

		The `FROM` instruction means that the [container](https://www.docker.com/what-container) is initialized from a bare installation of Ubuntu 18.04. You can check the versions of Ubuntu available [here](https://hub.docker.com/_/ubuntu/) or others operating systems like [debian](https://hub.docker.com/_/debian/) or [worst](https://hub.docker.com/r/microsoft/windowsservercore/).

		Then we declare the maintainer of the container. Before declaring an environment variable for the container named `KALLISTO_VERSION`, which contains the version of the tool wrapped. This this bash variable will be declared for the user root within the [container](https://www.docker.com/what-container).

		You should always declare a variable `TOOLSNAME_VERSION` that contains the version number of commit number of the tools you wrap. In simple cases you just have to modify this line to create a new `Dockerfile` for another version of the tool.

		The following lines of the [`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile) are a succession of `bash` commands executed as the root user within the container.
		Each `RUN` block is run sequentially by `Docker`. If there is an error or modifications in a `RUN` block, only this block and the following `RUN` will be executed.

		You can learn more about the building of Docker containers [here](https://docs.docker.com/engine/reference/builder/#usage).

		When you build your [`Dockerfile`](./src/docker_modules/kallisto/0.44.0/Dockerfile), instead of launching many times the [`docker_init.sh`](./src/docker_modules/kallisto/0.44.0/docker_init.sh) script to tests your [container](https://www.docker.com/what-container), you can connect to a base container in interactive mode to launch tests your commands.

		```sh
		docker run -it ubuntu:18.04 bash
		KALLISTO_VERSION=0.44.0
		```

		# SGE / [PSMN](http://www.ens-lyon.fr/PSMN/doku.php)

		To run easily tools on the [PSMN](http://www.ens-lyon.fr/PSMN/doku.php), you need to build your own [Environment Module](http://www.ens-lyon.fr/PSMN/doku.php?id=documentation:tools:modules).

		You can read the Contributing guide for the [PMSN/modules](https://gitlab.biologie.ens-lyon.fr/PSMN/modules) project [here](https://gitlab.biologie.ens-lyon.fr/PSMN/modules/blob/master/CONTRIBUTING.md)

		# Nextflow

		The last step to wrap your tool is to make it available in nextflow. For this you need to create at least 4 files, like the following for Kallisto version `0.44.0`:

		```sh
		ls -lR src/nf_modules/kallisto
		src/nf_modules/kallisto/:
		total 12
		-rw-r--r-- 1 laurent users 551 Jun 18 17:14 index.nf
		-rw-r--r-- 1 laurent users 901 Jun 18 17:14 mapping_paired.nf
		-rw-r--r-- 1 laurent users 1037 Jun 18 17:14 mapping_single.nf
		-rwxr-xr-x 1 laurent users 627 Jun 18 17:14 tests.sh*
		```

		The [`.config` files](./src/nf_modules/kallisto/) file contains instructions for two profiles : `psmn` and `docker`.
		The [`.nf` files](./src/nf_modules/kallisto/) file contains nextflow processes to use `Kallisto`.

		The [`tests/tests.sh`](./src/nf_modules/kallisto/tests/tests.sh) script (with executable rights), contains a series of nextflow calls on the other `.nf` files of the folder. Those tests correspond to execution of the `.nf` files present in the [`kallisto folder`](./src/nf_modules/kallisto/) on the [LBMC/tiny_dataset](https://gitlab.biologie.ens-lyon.fr/LBMC/tiny_dataset) dataset with the `docker` profile. You can read the Running the tests* section of the [README.md](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/README.md).

		## [`kallisto.config`](./src/nf_modules/kallisto/)

		The `.config` file defines the configuration to apply to your process conditionally to the value of the `-profile` option. You must define configuration for at least the `psmn` and `docker` profile.

		```Groovy
		profiles {
		docker {
		docker.temp = 'auto'
		docker.enabled = true
		process {
		}
		}
		psmn {
		process{
		}
		}
		```

		### `docker` profile

		The `docker` profile starts by enabling docker for the whole pipeline. After that you only have to define the container name for each process:
		For example, for `Kallisto` with the version `0.44.0`, we have:

		```Groovy
		process {
		withName: index_fasta {
		container = "kallisto:0.44.0"
		}
		withName: mapping_fastq {
		container = "kallisto:0.44.0"
		}
		}
		```

		### `psmn` profile

		The `psmn` profile defines for each process all the informations necessary to launch your process on a given queue with SGE at the [PSMN](http://www.ens-lyon.fr/PSMN/doku.php).
		For example, for `Kallisto`, we have:

		```Groovy
		process{
		withName: index_fasta {
		beforeScript = "source /usr/share/lmod/lmod/init/bash; module use ~/privatemodules"
		module = "Kallisto/0.44.0"
		executor = "sge"
		cpus = 16
		memory = "30GB"
		time = "24h"
		queue = 'E5-2670deb128A,E5-2670deb128B,E5-2670deb128C,E5-2670deb128D,E5-2670deb128E,E5-2670deb128F'
		penv = 'openmp16'
		}
		withName: mapping_fastq {
		beforeScript = "source /usr/share/lmod/lmod/init/bash; module use ~/privatemodules"
		module = "Kallisto/0.44.0"
		executor = "sge"
		cpus = 16
		memory = "30GB"
		time = "24h"
		queue = 'E5-2670deb128A,E5-2670deb128B,E5-2670deb128C,E5-2670deb128D,E5-2670deb128E,E5-2670deb128F'
		penv = 'openmp16'
		}
		}
		```

		The `beforeScript` variable is executed before the main script for the corresponding process.

		## [`kallisto.nf`](./src/nf_modules/kallisto/kallisto.nf)

		The [`kallisto.nf`](./src/nf_modules/kallisto/kallisto.nf) file contains examples of nextflow process that execute Kallisto.

		- Each example must be usable as it is to be incorporated in a nextflow pipeline.
		- You need to define, default value for the parameters passed to the process.
		- Input and output must be clearly defined.
		- Your process should be usable as a starting process or a process retrieving the output of another process.

		For more informations on processes and channels you can check the [nextflow documentation](https://www.nextflow.io/docs/latest/index.html).

		## Making your wrapper available to the LBMC

		To make your module available to the LBMC you must have a `tests.sh` script and one or many `docker_init.sh` scripts working without errors.
		All the processes in your `.nf` must be covered by the tests.

		After pushing your modifications on your forked repository, you can make a Merge Request to the [PSMN/modules](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow) dev branch. Where it will be tested and integrated to the master branch.

		You can read more on this process [here](https://guides.github.com/introduction/flow/)

doc/TP_experimental_biologists.md

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		## Available tools

		- nf module: a working example of nextflow process is available in `src/nf_modules/<tools>/<tool>.nf` and `src/nf_modules/<tools>/<tool>.config`
		- docker module: you can create a docker with the `src/docker_modules/<tool>/<version>/docker_init.sh`
		- psmn module: you can use the tool in the PSMN
		- IN2P3 module: you can use the tool in the CCIN2P3

		\| tool \| nf module \| docker module \| psmn module \| in2p3 module \|
		\|------\|:---------:\|:-------------:\|:-----------:\|:-------------:\|
		BEDtools \| ok \| ok \| ok \| ok
		BFCtools \|no \| ok \| ok \| ok
		bioawk \|no \| ok \| ok \| ok
		Bowtie \| ok \| ok \| no \| ok
		Bowtie2 \| ok \| ok \| ok \| ok
		BWA \| ok \| ok \| ok \| ok
		canu \| ok \| ok \| ok \| ok
		cutadapt \| ok \| ok \| ok \| ok
		deepTools \| ok \| ok \| ok \| ok
		fastp \| ok \| ok \| ok \| ok
		FastQC \| ok \| ok \| ok \| ok
		file_handle \| no \| ok \| ok \| ok
		GATK \| no \| ok \| ok \| ok
		HISAT2 \| ok \| ok \| ok \| ok
		HTSeq \| ok \| ok \| ok \| ok
		Kallisto \| ok \| ok \| ok \| ok
		MACS2 \| ok \| ok \| ok \| ok
		MultiQC \| ok \| ok \| ok \| ok
		MUSIC \| ok \| ok \| ok \| ok
		picard \| no \| ok \| ok \| ok
		pigz \| no \| ok \| ok \| ok
		RSEM \| ok \| ok \| ok \| ok
		Salmon \| no \| ok \| ok \| ok
		sambamba \| ok \| ok \| ok \| ok
		samblaster \| ok \| ok \| ok \| ok
		SAMtools \| ok \| ok \| ok \| ok
		SRAtoolkit \| ok \| ok \| ok \| ok
		subread \| no \| ok \| ok \| ok
		TopHat \| no \| ok \| ok \| ok
		Trimmomatic \| no \| ok \| ok \| ok
		UMItools \| no \| ok \| ok \| ok
		UrQt \| ok \| ok \| ok \| ok

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		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		# Building your own pipeline

		The goal of this guide is to walk you through the Nextflow pipeline building process you will learn:

		1. How to use this [git repository (LBMC/nextflow)](https://gitbio.ens-lyon.fr/LBMC/nextflow) as a template for your project.
		2. The basis of [Nextflow](https://www.nextflow.io/) the pipeline manager that we use at the lab.
		3. How to build a simple pipeline for the transcript-level quantification of RNASeq data
		4. How to run the exact same pipeline on a computing center ([PSMN](http://www.ens-lyon.fr/PSMN/doku.php))

		This guide assumes that you followed the [Git basis, training course](https://gitbio.ens-lyon.fr/LBMC/hub/formations/git_basis).

		# Initialize your own project

		You are going to build a pipeline for you or your team. So the first step is to create your own project.

		## Forking

		Instead of reinventing the wheel, you can use the [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) as a template.
		To easily do so, go to the [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) repository and click on the [fork](https://gitbio.ens-lyon.fr/LBMC/nextflow/forks/new) button (you need to log-in).

		![fork button](./img/fork.png)

		In git, the [action of forking](https://git-scm.com/book/en/v2/GitHub-Contributing-to-a-Project) means that you are going to make your own private copy of a repository.
		This repository will keep a link with the original [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) project from which you will be able to

		- [get updates](https://gitbio.ens-lyon.fr/LBMC/nextflow#getting-the-last-updates) `LBMC/nextflow` from the repository
		- propose update (see [contributing guide](https://gitbio.ens-lyon.fr/LBMC/nextflow/-/blob/master/CONTRIBUTING.md#forking))


		## Project organization

		This project (and yours) follows the [guide of good practices for the LBMC](http://www.ens-lyon.fr/LBMC/intranet/services-communs/pole-bioinformatique/ressources/good_practice_LBMC)

		You are now on the main page of your fork of the [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow). You can explore this project, all the codes in it is under the CeCILL licence (in the [LICENCE](https://gitbio.ens-lyon.fr/LBMC/nextflow/blob/master/LICENSE) file).

		The [README.md](https://gitbio.ens-lyon.fr/LBMC/nextflow/blob/master/README.md) file contains instructions to run your pipeline and test its installation.

		The [CONTRIBUTING.md](https://gitbio.ens-lyon.fr/LBMC/nextflow/blob/master/CONTRIBUTING.md) file contains guidelines if you want to contribute to the [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow).

		The [data](https://gitbio.ens-lyon.fr/LBMC/nextflow/tree/master/data) folder will be the place where you store the raw data for your analysis.
		The [results](https://gitbio.ens-lyon.fr/LBMC/nextflow/tree/master/results) folder will be the place where you store the results of your analysis.

		The content of `data` and `results` folders should never be saved on git.

		The [doc](https://gitbio.ens-lyon.fr/LBMC/nextflow/tree/master/doc) folder contains the documentation and this guide.

		And most interestingly for you, the [src](https://gitbio.ens-lyon.fr/LBMC/nextflow/tree/master/src) contains code to wrap tools. This folder contains one visible subdirectories `nf_modules` some pipeline examples and other hidden folders and files.

		# Nextflow pipeline

		A pipeline is a succession of [process](https://www.nextflow.io/docs/latest/process.html#process-page). Each `process` has data input(s) and optional data output(s). Data flows are modeled as [channels](https://www.nextflow.io/docs/latest/channel.html).

		## Processes

		Here is an example of process:

		```Groovy
		process sample_fasta {
		input:
		path fasta

		output:
		path "sample.fasta", emit: fasta_sample

		script:
		"""
		head ${fasta} > sample.fasta
		"""
		}
		```

		We have the process `sample_fasta` that takes fasta `path` input and as output a fasta `path`. The `process` task itself is defined in the `script:` block and within `"""`.

		```Groovy
		input:
		path fasta
		```

		When we zoom on the `input:` block, we see that we define a variable `fasta` of type `path`.
		This means that the `sample_fasta` `process` is going to get a flux of fasta file(s).
		Nextflow is going to write a file named as the content of the variable `fasta` in the root of the folder where `script:` is executed.

		```Groovy
		output:
		path "sample.fasta", emit: fasta_sample
		```

		At the end of the script, a file named `sample.fasta` is found in the root the folder where `script:` is executed and will be emitted as `fasta_sample`.

		Using the WebIDE of Gitlab, create a file `src/fasta_sampler.nf`
		![webide](./img/webide.png)

		The first line that you need to add is

		```Groovy
		nextflow.enable.dsl=2
		```

		Then add the `sample_fastq` process and commit it to your repository.


		## Workflow

		In Nexflow, `process` blocks are chained together within a `workflow` block.
		For the time being, we only have one `process` so `workflow` may look like an unnecessary complication, but keep in mind that we want to be able to write complex bioinformatic pipeline.

		```Groovy
		workflow {
		sample_fasta(fasta_file)
		}
		```

		Like `process` blocks `workflow` can take some inputs: `fasta_files`
		and transmit this input to `process`es

		```Groovy
		sample_fasta(fasta_file)
		```

		Add the definition of the `workflow` to the `src/fasta_sampler.nf` file and commit it to your repository.

		## Channels

		Why bother with `channel`s? In the above example, the advantages of `channel`s are not really clear. We could have just given the `fasta` file to the `workflow`. But what if we have many fasta files to process? What if we have sub processes to run on each of the sampled fasta files? Nextflow can easily deal with these problems with the help of `channel`s.

		> Channels are streams of items that are emitted by a source and consumed by a process. A process with a `channel` as input will be run on every item send through the `channel`.

		```Groovy
		channel
		.fromPath( "data/tiny_dataset/fasta/*.fasta" )
		.set { fasta_file }
		```

		Here we defined the `channel`, `fasta_file`, that is going to send every fasta file from the folder `data/tiny_dataset/fasta/` into the process that takes it as input.

		Add the definition of the `channel`, above the `workflow` block, to the `src/fasta_sampler.nf` file and commit it to your repository.

		## Run your pipeline locally

		After writing this first pipeline, you may want to test it. To do that, first clone your repository.
		After following the [Git basis, training course](https://gitbio.ens-lyon.fr/LBMC/hub/formations/git_basis), you should have an up-to-date `ssh` configuration to connect to the `gitbio.ens-lyon.fr` git server.

		You can run the following commands to download your project on your computer:

		```sh
		git clone git@gitbio.ens-lyon.fr:<usr_name>/nextflow.git
		cd nextflow
		src/install_nextflow.sh
		```

		We also need data to test our pipeline:

		```sh
		cd data
		git clone git@gitbio.ens-lyon.fr:LBMC/hub/tiny_dataset.git
		cd ..
		```

		We can run our pipeline with the following command:

		```sh
		./nextflow src/fasta_sampler.nf
		```


		## Getting your results

		Our pipeline seems to work but we don’t know where is the `sample.fasta`. To get results out of a `process`, we need to tell nextflow to write it somewhere (we may don’t need to get every intermediate file in our results).

		To do that we need to add the following line before the `input:` section:

		```Groovy
		publishDir "results/sampling/", mode: 'copy'
		```

		Every file described in the `output:` section will be copied from nextflow to the folder `results/sampling/`.

		Add this to your `src/fasta_sampler.nf` file with the WebIDE and commit to your repository.
		Pull your modifications locally with the command:

		```sh
		git pull origin master
		```

		You can run your pipeline again and check the content of the folder `results/sampling`.

		## Fasta everywhere

		We ran our pipeline on one fasta file. How would nextflow handle 100 of them? To test that we need to duplicate the `tiny_v2.fasta` file:

		```sh
		for i in {1..100}
		do
		cp data/tiny_dataset/fasta/tiny_v2.fasta data/tiny_dataset/fasta/tiny_v2_${i}.fasta
		done
		```

		You can run your pipeline again and check the content of the folder `results/sampling`.

		Every `fasta_sampler` process write a `sample.fasta` file. We need to make the name of the output file dependent of the name of the input file.

		```Groovy
		output:
		path "*_sample.fasta", emit: fasta_sample

		script:
		"""
		head ${fasta} > ${fasta.simpleName}_sample.fasta
		"""
		```

		Add this to your `src/fasta_sampler.nf` file with the WebIDE and commit it to your repository before pulling your modifications locally.
		You can run your pipeline again and check the content of the folder `results/sampling`.

		Congratulations you built your first, one step, nextflow pipeline !


		# Build your own RNASeq pipeline

		In this section you are going to build your own pipeline for RNASeq analysis from the code available in the `src/nf_modules` folder.

		Open the WebIDE and create a `src/RNASeq.nf` file.

		The first line that we are going to add is

		```Groovy
		nextflow.enable.dsl=2
		```

		## fastp

		The first step of the pipeline is to remove any Illumina adaptors left in your read files and to trim your reads by quality.

		The [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) template provide you with many tools, for which you can find a predefined `process` block.
		You can find a list of these tools in the [`src/nf_modules`](./src/nf_modules) folder.
		You can also ask for a new tool by creating a [new issue for it](https://gitbio.ens-lyon.fr/LBMC/nextflow/-/issues/new) in the [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) project.

		We are going to include the [`src/nf_modules/fastp/main.nf`](./src/nf_modules/fastp/main.nf) in our `src/RNASeq.nf` file

		```Groovy
		include { fastp } from "./nf_modules/fastp/main.nf"
		```
		The `./nf_modules/fastp/main.nf` is relative to the `src/RNASeq.nf` file, this is why we don’t include the `src/` part of the path.

		With this line we can call the `fastp` block in our future `workflow` without having to write it !
		If we check the content of the file [`src/nf_modules/fastp/main.nf`](./src/nf_modules/fastp/main.nf), we can see that by including `fastp`, we are including a sub-`workflow` (we will come back on this object latter). Sub-`workflow` can be used like `process`es.

		This `sub-workflow` takes a `fastq` `channel`. We need to make one:

		```Groovy
		channel
		.fromFilePairs( "data/tiny_dataset/fastq/*_R{1,2}.fastq", size: -1)
		.set { fastq_files }
		```

		The `.fromFilePairs()` function creates a `channel` of pairs of fastq files. Therefore, the items emitted by the `fastq_files` channel are going to be pairs of fastq for paired-end data.

		The option `size: -1` allows for arbitrary numbers of associated files. Therefore, we can use the same `channel` creation for single-end data.

		We can now include the `workflow` definition, passing the `fastq_files` `channel` to `fastp` to our `src/RNASeq.nf` file.

		```Groovy
		workflow {
		fastp(fastq_files)
		}
		```

		You can commit your `src/RNASeq.nf` file, `pull` your modification locally and run your pipeline with the command:

		```Groovy
		./nextflow src/RNASeq.nf
		```

		What is happening ?

		## Nextflow `-profile`

		Nextflow tells you the following error: `fastp: command not found`. You haven’t `fastp` installed on your computer.

		Tools installation can be a tedious process and reinstalling old version of those tools to reproduce old analyses can be very difficult.
		Containers technologies like [Docker](https://www.docker.com/) or [Singularity](https://sylabs.io/singularity/) create small virtual environments where we can install software in a given version with all it’s dependencies. This environment can be saved, and shared, to have access to this exact working version of the software.

		> Why two different systems ?

		> Docker is easy to use and can be installed on Windows / MacOS / GNU/Linux but need admin rights.
		> Singularity can only be used on GNU/Linux but don’t need admin rights, and can be used on shared environment.

		The [LBMC/nextflow](https://gitbio.ens-lyon.fr/LBMC/nextflow) template provides you with [4 different `-profile`s to run your pipeline](https://gitbio.ens-lyon.fr/LBMC/nextflow/-/blob/master/doc/getting_started.md#nextflow-profile).

		Profiles are defined in the [`src/nextflow.config`](./src/nextflow.config), which is the default configuration file for your pipeline (you don’t have to edit this file).

		To run the pipeline locally you can use the profile `singularity` or `docker`

		```Groovy
		./nextflow src/RNASeq.nf -profile singularity
		```

		The `fastp`, `singularity` or `docker`, image is downloaded automatically and the fastq files are processed.

		## Pipeline `--` arguments

		We have defined the fastq files path within our `src/RNASeq.nf` file.
		But what if we want to share our pipeline with someone who doesn’t want to analyze the `tiny_dataset` and but other fastq.
		We can define a variable instead of fixing the path.

		```Groovy
		params.fastq = "data/fastq/*_{1,2}.fastq"
		channel
		.fromFilePairs( params.fastq, size: -1)
		.set { fastq_files }
		```

		We declare a variable that contains the path of the fastq file to look for. The advantage of using `params.fastq` is that the option `--fastq` is now a parameter of your pipeline.

		Thus, you can call your pipeline with the `--fastq` option.

		You can commit your `src/RNASeq.nf` file, `pull` your modification locally and run your pipeline with the command:

		```sh
		./nextflow src/RNASeq.nf -profile singularity --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq"
		```

		We can also add the following line:

		```Groovy
		log.info "fastq files: ${params.fastq}"
		```

		This line simply displays the value of the variable

		## BEDtools

		We need the sequences of the transcripts that need to be quantified. We are going to extract these sequences from the reference `data/tiny_dataset/fasta/tiny_v2.fasta` with the `bed` file annotation `data/tiny_dataset/annot/tiny.bed`.

		You can include the `fasta_from_bed` `process` from the [src/nf_modules/bedtools/main.nf](https://gitbio.ens-lyon.fr/LBMC/nextflow/blob/master/src/nf_modules/bedtools/main.nf) file to your `src/RNASeq.nf` file.

		You need to be able to input a `fasta_files` `channel` and a `bed_files` `channel`.

		```Groovy
		log.info "fasta file : ${params.fasta}"
		log.info "bed file : ${params.bed}"

		channel
		.fromPath( params.fasta )
		.ifEmpty { error "Cannot find any fasta files matching: ${params.fasta}" }
		.map { it -> [it.simpleName, it]}
		.set { fasta_files }
		channel
		.fromPath( params.bed )
		.ifEmpty { error "Cannot find any bed files matching: ${params.bed}" }
		.map { it -> [it.simpleName, it]}
		.set { bed_files }
		```

		We introduce 2 new directives:
		- `.ifEmpty { error "Cannot find any fasta files matching: ${params.fasta}" }` to throw an error if the path of the file is not right
		- `.map { it -> [it.simpleName, it]}` to transform our `channel` to a format compatible with the [`CONTRIBUTING`](../CONTRIBUTING.md) rules. Item, in the `channel` have the following shape [file_id, [file]], like the ones emited by the `.fromFilePairs(..., size: -1)` function.

		We can add the `fastq_from_bed` step to our `workflow`

		```Groovy
		workflow {
		fastp(fastq_files)
		fasta_from_bed(fasta_files, bed_files)
		}
		```

		Commit your work and test your pipeline with the following command:

		```sh
		./nextflow src/RNASeq.nf -profile singularity --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq" --fasta "data/tiny_dataset/fasta/tiny_v2.fasta" --bed "data/tiny_dataset/annot/tiny.bed"
		```

		## Kallisto

		Kallisto run in two steps: the indexation of the reference and the quantification of the transcript on this index.

		You can include two `process`es with the following syntax:

		```Groovy
		include { index_fasta; mapping_fastq } from './nf_modules/kallisto/main.nf'
		```

		The `index_fasta` process needs to take as input the output of your `fasta_from_bed` `process`, which has the shape `[fasta_id, [fasta_file]]`.

		The input of your `mapping_fastq` `process` needs to take as input and the output of your `index_fasta` `process` and the `fastp` `process`, of shape `[index_id, [index_file]]`, and `[fastq_id, [fastq_r1_file, fastq_r2_file]]`.

		The output of a `process` is accessible through `<process_name>.out`.
		In the cases where we have an `emit: <channel_name>` we can access the corresponding channel with`<process_name>.out.<channel_name>`

		```Groovy
		workflow {
		fastp(fastq_files)
		fasta_from_bed(fasta_files, bed_files)
		index_fasta(fasta_from_bed.out.fasta)
		mapping_fastq(index_fasta.out.index.collect(), fastp.out.fastq)
		}
		```

		Commit your work and test your pipeline.

		## Returning results

		By default none of the `process` defined in `src/nf_modules` use the `publishDir` instruction.
		You can specify their `publishDir` directory by specifying the :

		```Groovy
		params.<process_name>_out = "path"
		```

		Where "path" will describe a path within the `results` folder

		Therefore you can either:

		- call your pipeline with the following parameter `--mapping_fastq_out "quantification/"`
		- add the following line to your `src/RNASeq.nf` file to get the output of the `mapping_fastq` process:

		```Groovy
		include { index_fasta; mapping_fastq } from './nf_modules/kallisto/main.nf' addParams(mapping_fastq_out: "quantification/")
		```

		Commit your work and test your pipeline.
		You now have a RNASeq analysis pipeline that can run locally with Docker or Singularity!

		## Bonus

		A file `report.html` is created for each run with the detail of your pipeline execution.
		You can use the `-resume` option to be able to save into cache the process results (the in a `work/` folder).

		# Run your RNASeq pipeline on the PSMN

		First you need to connect to the PSMN:

		```sh
		login@allo-psmn
		```
		Then once connected to `allo-psmn`, you can connect to `e5-2667v4comp1`:

		```sh
		login@m6142comp2
		```

		## Set your environment

		Create and go to your `scratch` folder:

		```sh
		mkdir -p /scratch/Bio/<login>
		cd /scratch/Bio/<login>
		```

		Then you need to clone your pipeline and get the data:

		```sh
		git clone https://gitbio.ens-lyon.fr/<usr_name>/nextflow.git
		cd nextflow/data
		git clone https://gitbio.ens-lyon.fr/LBMC/hub/tiny_dataset.git
		cd ..
		```

		## Run nextflow

		As we don’t want nextflow to be killed in case of disconnection, we start by launching `tmux`. In case of disconnection, you can restore your session with the command `tmux a` and close one with `ctr + b + d`

		```sh
		tmux
		src/install_nextflow.sh
		./nextflow src/RNASeq.nf -profile psmn --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq" --fasta "data/tiny_dataset/fasta/tiny_v2.fasta" --bed "data/tiny_dataset/annot/tiny.bed"
		```

		You just ran your pipeline on the PSMN!

doc/getting_started.md

+62 −23

Original line number	Diff line number	Diff line
		## Getting Started
		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		### Prerequisites
		# Getting Started

		To run nextflow on you computer you need to have java (>= 1.8) installed.
		These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
		You can follow the [building your pipeline guide](./doc/building_your_pipeline.md) to learn how to build your own pipelines.

		## Prerequisites

		To run nextflow on your computer you need to have `java` (>= 1.8) installed.

		```sh
		java --version
		```

		To be able to easily test tools already implemented for nextflow on your computer (`src/nf_modules/` to see their list). You need to have docker installed.
		and `git`

		```sh
		docker run hello-world
		git --version
		```

		### Installing

		To install nextflow on you computer simply run the following command:
		To be able to run existing tools in nextflow on your computer (`src/nf_modules/` to see the list). You need to have `docker` installed.

		```sh
		src/install_nextflow.sh
		docker run hello-world
		```

		Then to initialize a given tools run the following command:
		Alternatively if you are on Linux, you can use `singularity`:

		```sh
		src/docker_modules/<tool_name>/<tool_version>/docker_init.sh
		singularity run docker://hello-world
		```

		For example to initialize `file_handle` version `0.1.1`, run:
		## Installing

		```sh
		src/docker_modules/file_handle/0.1.1/docker_init.sh
		```
		To install nextflow on your computer simply run the following command:

		To initialize all the tools:
		```sh
		find src/docker_modules/ -name "docker_init.sh" \| awk '{system($0)}'
		git clone git@gitbio.ens-lyon.fr:LBMC/nextflow.git
		cd nextflow/
		src/install_nextflow.sh
		```

		## Running the tests
		## Running a toy RNASeq quantification pipeline

		To run tests we first need to get a training set

		```sh
		cd data
		git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/LBMC/tiny_dataset.git
		git clone https://gitbio.ens-lyon.fr/LBMC/Hub/tiny_dataset.git
		cp tiny_dataset/fastq/tiny_R1.fastq tiny_dataset/fastq/tiny2_R1.fastq
		cp tiny_dataset/fastq/tiny_R2.fastq tiny_dataset/fastq/tiny2_R2.fastq
		cp tiny_dataset/fastq/tiny_S.fastq tiny_dataset/fastq/tiny2_S.fastq
		@@ -56,11 +61,45 @@ cd ..
		Then to run the tests for a given tools run the following command:

		```sh
		src/nf_modules/<tool_name>/<tool_version>/tests.sh
		./nextflow src/solution_RNASeq.nf --fastq "data/tiny_dataset/fastq/tiny2_R{1,2}.fastq.gz" --fasta "data/tiny_dataset/fasta/tiny_v2_10.fasta" --bed "data/tiny_dataset/annot/tiny.bed" -profile docker
		```

		## Nextflow profile

		By default le `src/nextflow.config` file define 4 different profiles

		- `-profile docker` each process of the pipeline will be executed within a `docker` container locally
		- `-profile singularity` each process of the pipeline will be executed within a `singularity` container locally
		- `-profile psmn` each process will be sent as a separate job within a `charliecloud` container on the PSMN
		- `-profile ccin2p3` each process will be sent as a separate job within a `singularity` container on the CCIN2P3

		If the containers are not found locally, they are automatically downloaded before running the process. For the PSMN and CCIN2P3, the `singularity` images are downloaded in a shared folder (`/scratch/Bio/charliecloud` for the PSMN, and `/sps/lbmc/common/singularity/` for the CCIN2P3)

		### PSMN

		To have access to `charliecloud` on the PSMN you need to add the followin path to your `PATH` variable:

		```sh
		PATH=/Xnfs/abc/charliecloud_bin/:$PATH
		```

		For example to run the tests on `Bowtie2` run:
		You can add this line in your `~/.bashrc` or `~/.zshrc` file

		When running `nextflow` on the PSMN, we recommend to use `tmux` before launching the pipeline:

		```sh
		tmux
		./nextflow src/solution_RNASeq.nf --fastq "data/tiny_dataset/fastq/tiny2_R{1,2}.fastq.gz" --fasta "data/tiny_dataset/fasta/tiny_v2_10.fasta" --bed "data/tiny_dataset/annot/tiny.bed" -profile psmn
		```

		Therefore, the `nextflow` process will continue to run even if you are disconnected.
		You can re-attach the `tmux` session, with the command `tmux a` (and press `ctrl` `+` `b` `+` `d` to detach the attached session).

		### CCIN2P3

		When runnning `nextflow` on the CCIN2P3, you cannot use `tmux`, instead you should send a _daemon_ jobs which will launch the `nextflow` command.
		You can edit the `src/ccin2p3.pbs` file to personalize your `nextflow` command and send it with the command:

		```sh
		src/nf_modules/bowtie2/tests.sh
		qsub src/ccin2p3.pbs
		```

doc/img/fork.png.license

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		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0

doc/img/merge_request.png.license

0 → 100644

+3 −0

Original line number	Diff line number	Diff line
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0

doc/img/webide.png.license

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		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0

doc/mail.txt

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		@@ -19,3 +19,24 @@ If you want to work on your laptop, or plan to work remotely on your desktop via
		- docker

		Best,

		Dear all,

		You registered to the formation Git (12/12) or/and the formation Nextlflow (13/12) from 13:30 pm to 18pm in the in the room M7.1H04.

		Please check that you have an account on our gitlab server at the following url :
		https://gitlab.biologie.ens-lyon.fr (only available from the ENS network)
		To connect, simply click on the CAS button.
		Your account is now linked to the gitlab server, but blocked
		You can send an email to laurent.modolo@ens-lyon.fr to activate your account.

		You will also need an account on the PSMN (http://www.ens-lyon.fr/PSMN/doku.php?id=contact:forms:inscription) (don’t wait until the 12 to request an account !)

		If you want to work on your laptop, or plan to work remotely on your desktop via ssh (http://www.ens-lyon.fr/LBMC/intranet/services-communs/pole-bioinformatique/bioinfo_club/1_ssh_and_other_tools_to_work_remotly) you need to have the following software installed :
		- ssh
		- git
		- java (>=1.8) (for the nextflow formation)
		- docker (for the nextflow formation)
		Otherwise, you will need to request an account to use the computer in the room (http://www.cbp.ens-lyon.fr/doku.php?id=contact:compte)

		Best,

doc/mail.txt.license

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		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0

doc/nf_projects.md

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		<!--
		SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>

		SPDX-License-Identifier: CC-BY-SA-4.0
		-->

		## Projects using nextflow

		This page list existing Nextflow based pipeline projects into different categories

		- [RNASeq](./nf_projects.md#rnaseq)
		- [scRNASeq](./nf_projects.m#scrnaseq)
		- [DNASeq](./nf_projects.md#dnaseq)
		- [ChipSeq](./nf_projects.md#chipseq)

		To add your project to this list, please fork this project, modify this file and make a merge request.
		![merge request button](./img/merge_request.png)

		### RNASeq

		- [https://_https://gitlab.biologie.ens-lyon.fr/gylab/salmoninyeast](https://_https://gitlab.biologie.ens-lyon.fr/gylab/salmoninyeast)
		- [https://github.com/LBMC/readthroughpombe](https://github.com/LBMC/readthroughpombe)
		- [https://_https://gitlab.biologie.ens-lyon.fr/vvanoost/nextflow](https://_https://gitlab.biologie.ens-lyon.fr/vvanoost/nextflow)
		- [https://gitlab.biologie.ens-lyon.fr/elabaron/HIV_project](https://gitlab.biologie.ens-lyon.fr/elabaron/HIV_project)
		- [https://gitbio.ens-lyon.fr/LBMC/Palladino/RNAseq_nextflow](https://gitbio.ens-lyon.fr/LBMC/Palladino/RNAseq_nextflow)

		### single-cell RNA_-Seq
		### scRNASeq

		- [https://gitlab.com/LBMC_UMR5239/sbdm/mars-seq](https://gitlab.com/LBMC_UMR5239/sbdm/mars-seq)

		### DNASeq

		- [https://github.com/LBMC/ChrSexebelari](https://github.com/LBMC/ChrSexebelari)
		- [https://gitbio.ens-lyon.fr/LBMC/gylab/MappingNoise](https://gitbio.ens-lyon.fr/LBMC/gylab/MappingNoise)
		- [https://gitbio.ens-lyon.fr/LBMC/qrg/droso_hic_group/droso_haplo_rna_seq](https://gitbio.ens-lyon.fr/LBMC/qrg/droso_hic_group/droso_haplo_rna_seq)

		### Chip-Seq

		- [https://gitlab.biologie.ens-lyon.fr/Auboeuf/ChIP-seq](https://gitlab.biologie.ens-lyon.fr/Auboeuf/ChIP-seq)
		- [https://gitbio.ens-lyon.fr/LBMC/Bernard/quantitative-nucleosome-analysis](https://gitbio.ens-lyon.fr/LBMC/Bernard/quantitative-nucleosome-analysis)

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		*

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		source src/.conda_psmn.sh
		CONDA_ENVS=src/.conda_envs/
		if [ ! -d ${CONDA_ENVS}pigz_2.3.4 ]; then
		conda create --yes --name pigz_2.3.4 pigz=2.3.4
		fi
		if [ ! -d ${CONDA_ENVS}tophat_2.1.1 ]; then
		conda create --yes --name tophat_2.1.1 tophat=2.1.1
		fi
		if [ ! -d ${CONDA_ENVS}hisat2_2.0.0 ]; then
		conda create --yes --name hisat2_2.0.0 hisat2=2.0.0 samtools=1.7
		fi
		if [ ! -d ${CONDA_ENVS}hisat2_2.1.0 ]; then
		conda create --yes --name hisat2_2.1.0 hisat2=2.1.0 samtools=1.7
		fi
		if [ ! -d ${CONDA_ENVS}rsem_1.3.1 ]; then
		conda create --yes --name rsem_1.3.1 rsem=1.3.1 samtools=1.3
		fi
		if [ ! -d ${CONDA_ENVS}rsem_1.3.0 ]; then
		conda create --yes --name rsem_1.3.0 rsem=1.3.0 samtools=1.3
		fi
		if [ ! -d ${CONDA_ENVS}samblaster_0.1.24 ]; then
		conda create --yes --name samblaster_0.1.24 samblaster=0.1.24
		fi
		if [ ! -d ${CONDA_ENVS}nextflow_0.25.1 ]; then
		conda create --yes --name nextflow_0.25.1 nextflow=0.25.1
		fi
		if [ ! -d ${CONDA_ENVS}nextflow_19.01.0 ]; then
		conda create --yes --name nextflow_19.01.0 nextflow=19.01.0
		fi
		if [ ! -d ${CONDA_ENVS}nextflow_0.32.0 ]; then
		conda create --yes --name nextflow_0.32.0 nextflow=0.32.0
		fi
		if [ ! -d ${CONDA_ENVS}nextflow_0.28.2 ]; then
		conda create --yes --name nextflow_0.28.2 nextflow=0.28.2
		fi
		if [ ! -d ${CONDA_ENVS}samtools_1.7 ]; then
		conda create --yes --name samtools_1.7 samtools=1.7
		fi
		if [ ! -d ${CONDA_ENVS}samtools_1.5 ]; then
		conda create --yes --name samtools_1.5 samtools=1.5
		fi
		if [ ! -d ${CONDA_ENVS}bowtie2_2.3.2 ]; then
		conda create --yes --name bowtie2_2.3.2 bowtie2=2.3.2 samtools=1.7
		fi
		if [ ! -d ${CONDA_ENVS}bowtie2_2.3.4.1 ]; then
		conda create --yes --name bowtie2_2.3.4.1 bowtie2=2.3.4.1 samtools=1.7 #&& \
		fi
		if [ ! -d ${CONDA_ENVS}sra-tools_2.8.2 ]; then
		conda create --yes --name sra-tools_2.8.2 sra-tools=2.8.2
		fi
		if [ ! -d ${CONDA_ENVS}trimmomatic_0.36 ]; then
		conda create --yes --name trimmomatic_0.36 trimmomatic=0.36
		fi
		if [ ! -d ${CONDA_ENVS}trimmomatic_0.39 ]; then
		conda create --yes --name trimmomatic_0.39 trimmomatic=0.39
		fi
		if [ ! -d ${CONDA_ENVS}Python_3.6.1 ]; then
		conda create --yes --name Python_3.6.1 Python=3.6.1
		fi
		if [ ! -d ${CONDA_ENVS}Python_2.7.13 ]; then
		conda create --yes --name Python_2.7.13 Python=2.7.13
		fi
		if [ ! -d ${CONDA_ENVS}kallisto_0.44.0 ]; then
		conda create --yes --name kallisto_0.44.0 kallisto=0.44.0
		fi
		if [ ! -d ${CONDA_ENVS}kallisto_0.43.1 ]; then
		conda create --yes --name kallisto_0.43.1 kallisto=0.43.1
		fi
		if [ ! -d ${CONDA_ENVS}music_1.0.0 ]; then
		conda create --yes --name music_1.0.0 music=1.0.0
		fi
		if [ ! -d ${CONDA_ENVS}umitools_0.3.4 ]; then
		conda create --yes --name umitools_0.3.4 umitools=0.3.4
		fi
		if [ ! -d ${CONDA_ENVS}fastp_0.19.7 ]; then
		conda create --yes --name fastp_0.19.7 fastp=0.19.7
		fi
		if [ ! -d ${CONDA_ENVS}gatk_3.8 ]; then
		conda create --yes --name gatk_3.8 gatk=3.8
		fi
		if [ ! -d ${CONDA_ENVS}cutadapt_1.14 ]; then
		conda create --yes --name cutadapt_1.14 cutadapt=1.14
		fi
		if [ ! -d ${CONDA_ENVS}bioawk_1.0 ]; then
		conda create --yes --name bioawk_1.0 bioawk=1.0
		fi
		if [ ! -d ${CONDA_ENVS}canu_1.7 ]; then
		conda create --yes --name canu_1.7 canu=1.7
		fi
		if [ ! -d ${CONDA_ENVS}fastqc_0.11.5 ]; then
		conda create --yes --name fastqc_0.11.5 fastqc=0.11.5
		fi
		if [ ! -d ${CONDA_ENVS}bedtools_2.25.0 ]; then
		conda create --yes --name bedtools_2.25.0 bedtools=2.25.0
		fi
		if [ ! -d ${CONDA_ENVS}macs2_2.1.2 ]; then
		conda create --yes --name macs2_2.1.2 macs2=2.1.2
		fi
		if [ ! -d ${CONDA_ENVS}bcftools_1.7 ]; then
		conda create --yes --name bcftools_1.7 bcftools=1.7
		fi
		if [ ! -d ${CONDA_ENVS}salmon_0.8.2 ]; then
		conda create --yes --name salmon_0.8.2 salmon=0.8.2
		fi
		if [ ! -d ${CONDA_ENVS}urqt_d62c1f8 ]; then
		conda create --yes --name urqt_d62c1f8 urqt=d62c1f8
		fi
		if [ ! -d ${CONDA_ENVS}multiqc_0.9 ]; then
		conda create --yes --name multiqc_0.9 multiqc=0.9
		fi
		if [ ! -d ${CONDA_ENVS}multiqc_1.7 ]; then
		conda create --yes --name multiqc_1.7 multiqc=1.7
		fi
		if [ ! -d ${CONDA_ENVS}multiqc_1.0 ]; then
		conda create --yes --name multiqc_1.0 multiqc=1.0
		fi
		if [ ! -d ${CONDA_ENVS}cdhit_4.6.8 ]; then
		conda create --yes --name cdhit_4.6.8 cdhit=4.6.8
		fi
		if [ ! -d ${CONDA_ENVS}deeptools_3.0.2 ]; then
		conda create --yes --name deeptools_3.0.2 deeptools=3.0.2
		fi
		if [ ! -d ${CONDA_ENVS}htseq_0.9.1 ]; then
		conda create --yes --name htseq_0.9.1 htseq=0.9.1
		fi
		if [ ! -d ${CONDA_ENVS}htseq_0.11.2 ]; then
		conda create --yes --name htseq_0.11.2 htseq=0.11.2
		fi
		if [ ! -d ${CONDA_ENVS}R_3.4.3 ]; then
		conda create --yes --name R_3.4.3 R=3.4.3
		fi
		if [ ! -d ${CONDA_ENVS}R_3.3.1 ]; then
		conda create --yes --name R_3.3.1 R=3.3.1
		fi
		if [ ! -d ${CONDA_ENVS}file_handle_0.1.1 ]; then
		conda create --yes --name file_handle_0.1.1 file_handle=0.1.1
		fi
		if [ ! -d ${CONDA_ENVS}ncdu_1.13 ]; then
		conda create --yes --name ncdu_1.13 ncdu=1.13
		fi
		if [ ! -d ${CONDA_ENVS}picard_2.18.11 ]; then
		conda create --yes --name picard_2.18.11 picard=2.18.11
		fi
		if [ ! -d ${CONDA_ENVS}sambamba_0.6.7 ]; then
		conda create --yes --name sambamba_0.6.7 sambamba=0.6.7
		fi
		if [ ! -d ${CONDA_ENVS}star_2.7.3a ]; then
		conda create --yes --name star_2.7.3a star=2.7.3a
		fi

src/.conda_psmn.sh

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		/Xnfs/lbmcdb/common/conda/init.sh
		No newline at end of file

src/.docker_modules/CITE-seq-Count/1.4.5/Dockerfile

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		FROM ubuntu:22.04

		ENV CITESEQ_VERSION=1.4.5
		ENV PACKAGES procps locales gcc libstdc++-10-dev libcurl4 libc6 python3 python3-pip python3-dev

		RUN apt-get update && \
		apt-get install -y --no-install-recommends ${PACKAGES} && \
		apt-get clean

		RUN locale-gen en_US.UTF-8
		ENV LC_ALL=en_US.utf-8
		ENV LANG=en_US.utf-8
		ENV LC_ALL=C.UTF-8
		ENV LANG=C.UTF-8


		RUN pip3 install CITE-seq-Count==${CITESEQ_VERSION}

src/.docker_modules/CITE-seq-Count/1.4.5/docker_init.sh

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Original line number	Diff line number	Diff line
		#!/bin/sh

		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		docker pull lbmc/cite_seq_count:1.4.5
		docker build src/.docker_modules/CITE-seq-Count/1.4.5 -t 'lbmc/cite_seq_count:1.4.5'
		docker push lbmc/cite_seq_count:1.4.5
		# docker buildx build --platform linux/amd64,linux/arm64 -t "lbmc/cite_seq_count:1.4.5" --push src/.docker_modules/CITE-seq-Count/1.4.5

src/.docker_modules/CITE-seq-Count/1.5.0/Dockerfile

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Original line number	Diff line number	Diff line
		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		FROM ubuntu:22.04

		ENV PACKAGES procps locales gcc libstdc++-10-dev libcurl4 libc6 python3 python3-pip python3-dev git

		RUN apt-get update && \
		apt-get install -y --no-install-recommends ${PACKAGES} && \
		apt-get clean

		RUN locale-gen en_US.UTF-8
		ENV LC_ALL=en_US.utf-8
		ENV LANG=en_US.utf-8
		ENV LC_ALL=C.UTF-8
		ENV LANG=C.UTF-8

		RUN git clone https://github.com/Hoohm/CITE-seq-Count.git \
		&& cd CITE-seq-Count \
		&& git checkout 1.5.0-alpha \
		&& pip3 install requests pooch \
		&& pip3 install ./

src/.docker_modules/CITE-seq-Count/1.5.0/docker_init.sh

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		#!/bin/sh

		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		docker pull lbmc/cite_seq_count:1.5.0
		docker build src/.docker_modules/CITE-seq-Count/1.5.0 -t 'lbmc/cite_seq_count:1.5.0'
		docker push lbmc/cite_seq_count:1.5.0
		# docker buildx build --platform linux/amd64,linux/arm64 -t "lbmc/cite_seq_count:1.5.0" --push src/.docker_modules/CITE-seq-Count/1.5.0

src/.docker_modules/agat/0.8.0/Dockerfile

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		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		FROM quay.io/biocontainers/agat:0.8.0--pl5262hdfd78af_0
		No newline at end of file

src/.docker_modules/agat/0.8.0/docker_init.sh

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		#!/bin/sh

		# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
		#
		# SPDX-License-Identifier: AGPL-3.0-or-later

		docker pull lbmc/agat:0.8.0
		# docker build src/.docker_modules/agat/0.8.0 -t 'lbmc/agat:0.8.0'
		# docker push lbmc/agat:0.8.0
		docker buildx build --platform linux/amd64,linux/arm64 -t "lbmc/agat:0.8.0" --push src/.docker_modules/agat/0.8.0

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src/.docker_modules/bowtie/1.2.2/Dockerfile

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Original line number	Diff line number	Diff line
		## Available tools

		- nf module: a working example of nextflow process is available in `src/nf_modules/<tools>/<tool>.nf` and `src/nf_modules/<tools>/<tool>.config`
		- docker module: you can create a docker with the `src/docker_modules/<tool>/<version>/docker_init.sh`
		- psmn module: you can use the tool in the PSMN
		- IN2P3 module: you can use the tool in the CCIN2P3

		\| tool \| nf module \| docker module \| psmn module \| in2p3 module \|
		\|------\|:---------:\|:-------------:\|:-----------:\|:-------------:\|
		BEDtools \| ok \| ok \| ok \| ok
		BFCtools \|no \| ok \| ok \| ok
		bioawk \|no \| ok \| ok \| ok
		Bowtie \| ok \| ok \| no \| ok
		Bowtie2 \| ok \| ok \| ok \| ok
		BWA \| ok \| ok \| ok \| ok
		canu \| ok \| ok \| ok \| ok
		cutadapt \| ok \| ok \| ok \| ok
		deepTools \| ok \| ok \| ok \| ok
		fastp \| ok \| ok \| ok \| ok
		FastQC \| ok \| ok \| ok \| ok
		file_handle \| no \| ok \| ok \| ok
		GATK \| no \| ok \| ok \| ok
		HISAT2 \| ok \| ok \| ok \| ok
		HTSeq \| ok \| ok \| ok \| ok
		Kallisto \| ok \| ok \| ok \| ok
		MACS2 \| ok \| ok \| ok \| ok
		MultiQC \| ok \| ok \| ok \| ok
		MUSIC \| ok \| ok \| ok \| ok
		picard \| no \| ok \| ok \| ok
		pigz \| no \| ok \| ok \| ok
		RSEM \| ok \| ok \| ok \| ok
		Salmon \| no \| ok \| ok \| ok
		sambamba \| ok \| ok \| ok \| ok
		samblaster \| ok \| ok \| ok \| ok
		SAMtools \| ok \| ok \| ok \| ok
		SRAtoolkit \| ok \| ok \| ok \| ok
		subread \| no \| ok \| ok \| ok
		TopHat \| no \| ok \| ok \| ok
		Trimmomatic \| no \| ok \| ok \| ok
		UMItools \| no \| ok \| ok \| ok
		UrQt \| ok \| ok \| ok \| ok

Source

Target

Files

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