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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
[submodule "src/sge_modules"]
path = src/sge_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
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: ...
<!--
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,...)
- singularity support at in2p3 with `-profile in2p3`
- conda support at in2p3 with `-profile in2p3_conda`
## [0.2.9] - 2019-03-26
### Added
- Add new tools (fastq, macs2, umitools, ...)
- singularity support
### Changed
- every tool name is now in lowercase in each module section
## [0.2.7] - 2018-10-23
### Added
- Add new tools (BWA, GATK, sambamba, ...)
### Changed
- `sge` profile is now called `psmn` profile to prepare tests in the CCIN2P3
- every `psmn` config file has an update configuration for mono or 16 cpus queues
- update process naming to follow new nextflow format
## [0.2.6] - 2018-08-23
### Added
- Added `src/training_dataset.nf` to build a small training dataset from NGS data
### Changed
- the structure of `src/nf_modules`: the `tests` folder was removed
## [0.2.5] - 2018-08-22
### Added
- This fine changelog
### Changed
- the structure of `src/nf_modules`: the `tests` folder was removed
## [0.2.4] - 2018-08-02
### Changed
- add `paired_id` variable in the output of every single-end data processes to match the paired output
## [0.2.3] - 2018-07-25
### Added
- List of tools available as nextflow, docker or sge module to the `README.md`
## [0.2.2] - 2018-07-23
### Added
- SRA module from cigogne/nextflow-master 52b510e48daa1fb7
## [0.2.1] - 2018-07-23
### Added
- List of tools available as nextflow, docker or sge module
## [0.2.0] - 2018-06-18
### Added
- `doc/TP_computational_biologists.md`
- Kallisto/0.44.0
### Changed
- add `paired_id` variable in the output of every paired data processes
- BEDtools: fixes for fasta handling
- UrQt: fix git version in Docker
## [0.1.2] - 2018-06-18
### Added
- `doc/tp_experimental_biologist.md` and Makefile to build the pdf
- tests files for BEDtools
### Changed
- Kallisto: various fixes
- UrQt: improve output and various fixes
### Removed
- `src/nf_test.config` modules have their own `.config`
## [0.1.2] - 2018-06-18
### Added
- `doc/tp_experimental_biologist.md` and Makefile to build the pdf
- tests files for BEDtools
### Changed
- Kallisto: various fixes
- UrQt: improve output and various fixes
### Removed
- `src/nf_test.config` modules have their own `.config`
## [0.1.0] - 2018-05-06
This is the first working version of the repository as a nextflow module repository
<!--
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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Licensee of a non-exclusive, transferable and worldwide license for the
Software as set forth in Article 5 <#scope> hereinafter for the whole
term of the protection granted by the rights over said Software.
Article 3 - ACCEPTANCE
3.1 The Licensee shall be deemed as having accepted the terms and
conditions of this Agreement upon the occurrence of the first of the
following events:
* (i) loading the Software by any or all means, notably, by
downloading from a remote server, or by loading from a physical medium;
* (ii) the first time the Licensee exercises any of the rights granted
hereunder.
3.2 One copy of the Agreement, containing a notice relating to the
characteristics of the Software, to the limited warranty, and to the
fact that its use is restricted to experienced users has been provided
to the Licensee prior to its acceptance as set forth in Article 3.1
<#accepting> hereinabove, and the Licensee hereby acknowledges that it
has read and understood it.
Article 4 - EFFECTIVE DATE AND TERM
4.1 EFFECTIVE DATE
The Agreement shall become effective on the date when it is accepted by
the Licensee as set forth in Article 3.1 <#accepting>.
4.2 TERM
The Agreement shall remain in force for the entire legal term of
protection of the economic rights over the Software.
Article 5 - SCOPE OF RIGHTS GRANTED
The Licensor hereby grants to the Licensee, who accepts, the following
rights over the Software for any or all use, and for the term of the
Agreement, on the basis of the terms and conditions set forth hereinafter.
Besides, if the Licensor owns or comes to own one or more patents
protecting all or part of the functions of the Software or of its
components, the Licensor undertakes not to enforce the rights granted by
these patents against successive Licensees using, exploiting or
modifying the Software. If these patents are transferred, the Licensor
undertakes to have the transferees subscribe to the obligations set
forth in this paragraph.
5.1 RIGHT OF USE
The Licensee is authorized to use the Software, without any limitation
as to its fields of application, with it being hereinafter specified
that this comprises:
1. permanent or temporary reproduction of all or part of the Software
by any or all means and in any or all form.
2. loading, displaying, running, or storing the Software on any or all
medium.
3. entitlement to observe, study or test its operation so as to
determine the ideas and principles behind any or all constituent
elements of said Software. This shall apply when the Licensee
carries out any or all loading, displaying, running, transmission or
storage operation as regards the Software, that it is entitled to
carry out hereunder.
5.2 ENTITLEMENT TO MAKE CONTRIBUTIONS
The right to make Contributions includes the right to translate, adapt,
arrange, or make any or all modifications to the Software, and the right
to reproduce the resulting software.
The Licensee is authorized to make any or all Contributions to the
Software provided that it includes an explicit notice that it is the
author of said Contribution and indicates the date of the creation thereof.
5.3 RIGHT OF DISTRIBUTION
In particular, the right of distribution includes the right to publish,
transmit and communicate the Software to the general public on any or
all medium, and by any or all means, and the right to market, either in
consideration of a fee, or free of charge, one or more copies of the
Software by any means.
The Licensee is further authorized to distribute copies of the modified
or unmodified Software to third parties according to the terms and
conditions set forth hereinafter.
5.3.1 DISTRIBUTION OF SOFTWARE WITHOUT MODIFICATION
The Licensee is authorized to distribute true copies of the Software in
Source Code or Object Code form, provided that said distribution
complies with all the provisions of the Agreement and is accompanied by:
1. a copy of the Agreement,
2. a notice relating to the limitation of both the Licensor's warranty
and liability as set forth in Articles 8 and 9,
and that, in the event that only the Object Code of the Software is
redistributed, the Licensee allows effective access to the full Source
Code of the Software for a period of at least three years from the
distribution of the Software, it being understood that the additional
acquisition cost of the Source Code shall not exceed the cost of the
data transfer.
5.3.2 DISTRIBUTION OF MODIFIED SOFTWARE
When the Licensee makes a Contribution to the Software, the terms and
conditions for the distribution of the resulting Modified Software
become subject to all the provisions of this Agreement.
The Licensee is authorized to distribute the Modified Software, in
source code or object code form, provided that said distribution
complies with all the provisions of the Agreement and is accompanied by:
1. a copy of the Agreement,
2. a notice relating to the limitation of both the Licensor's warranty
and liability as set forth in Articles 8 and 9,
and, in the event that only the object code of the Modified Software is
redistributed,
3. a note stating the conditions of effective access to the full source
code of the Modified Software for a period of at least three years
from the distribution of the Modified Software, it being understood
that the additional acquisition cost of the source code shall not
exceed the cost of the data transfer.
5.3.3 DISTRIBUTION OF EXTERNAL MODULES
When the Licensee has developed an External Module, the terms and
conditions of this Agreement do not apply to said External Module, that
may be distributed under a separate license agreement.
5.3.4 COMPATIBILITY WITH OTHER LICENSES
The Licensee can include a code that is subject to the provisions of one
of the versions of the GNU GPL, GNU Affero GPL and/or EUPL in the
Modified or unmodified Software, and distribute that entire code under
the terms of the same version of the GNU GPL, GNU Affero GPL and/or EUPL.
The Licensee can include the Modified or unmodified Software in a code
that is subject to the provisions of one of the versions of the GNU GPL,
GNU Affero GPL and/or EUPL and distribute that entire code under the
terms of the same version of the GNU GPL, GNU Affero GPL and/or EUPL.
Article 6 - INTELLECTUAL PROPERTY
6.1 OVER THE INITIAL SOFTWARE
The Holder owns the economic rights over the Initial Software. Any or
all use of the Initial Software is subject to compliance with the terms
and conditions under which the Holder has elected to distribute its work
and no one shall be entitled to modify the terms and conditions for the
distribution of said Initial Software.
The Holder undertakes that the Initial Software will remain ruled at
least by this Agreement, for the duration set forth in Article 4.2 <#term>.
6.2 OVER THE CONTRIBUTIONS
The Licensee who develops a Contribution is the owner of the
intellectual property rights over this Contribution as defined by
applicable law.
6.3 OVER THE EXTERNAL MODULES
The Licensee who develops an External Module is the owner of the
intellectual property rights over this External Module as defined by
applicable law and is free to choose the type of agreement that shall
govern its distribution.
6.4 JOINT PROVISIONS
The Licensee expressly undertakes:
1. not to remove, or modify, in any manner, the intellectual property
notices attached to the Software;
2. to reproduce said notices, in an identical manner, in the copies of
the Software modified or not.
The Licensee undertakes not to directly or indirectly infringe the
intellectual property rights on the Software of the Holder and/or
Contributors, and to take, where applicable, vis-à-vis its staff, any
and all measures required to ensure respect of said intellectual
property rights of the Holder and/or Contributors.
Article 7 - RELATED SERVICES
7.1 Under no circumstances shall the Agreement oblige the Licensor to
provide technical assistance or maintenance services for the Software.
However, the Licensor is entitled to offer this type of services. The
terms and conditions of such technical assistance, and/or such
maintenance, shall be set forth in a separate instrument. Only the
Licensor offering said maintenance and/or technical assistance services
shall incur liability therefor.
7.2 Similarly, any Licensor is entitled to offer to its licensees, under
its sole responsibility, a warranty, that shall only be binding upon
itself, for the redistribution of the Software and/or the Modified
Software, under terms and conditions that it is free to decide. Said
warranty, and the financial terms and conditions of its application,
shall be subject of a separate instrument executed between the Licensor
and the Licensee.
Article 8 - LIABILITY
8.1 Subject to the provisions of Article 8.2, the Licensee shall be
entitled to claim compensation for any direct loss it may have suffered
from the Software as a result of a fault on the part of the relevant
Licensor, subject to providing evidence thereof.
8.2 The Licensor's liability is limited to the commitments made under
this Agreement and shall not be incurred as a result of in particular:
(i) loss due the Licensee's total or partial failure to fulfill its
obligations, (ii) direct or consequential loss that is suffered by the
Licensee due to the use or performance of the Software, and (iii) more
generally, any consequential loss. In particular the Parties expressly
agree that any or all pecuniary or business loss (i.e. loss of data,
loss of profits, operating loss, loss of customers or orders,
opportunity cost, any disturbance to business activities) or any or all
legal proceedings instituted against the Licensee by a third party,
shall constitute consequential loss and shall not provide entitlement to
any or all compensation from the Licensor.
Article 9 - WARRANTY
9.1 The Licensee acknowledges that the scientific and technical
state-of-the-art when the Software was distributed did not enable all
possible uses to be tested and verified, nor for the presence of
possible defects to be detected. In this respect, the Licensee's
attention has been drawn to the risks associated with loading, using,
modifying and/or developing and reproducing the Software which are
reserved for experienced users.
The Licensee shall be responsible for verifying, by any or all means,
the suitability of the product for its requirements, its good working
order, and for ensuring that it shall not cause damage to either persons
or properties.
9.2 The Licensor hereby represents, in good faith, that it is entitled
to grant all the rights over the Software (including in particular the
rights set forth in Article 5 <#scope>).
9.3 The Licensee acknowledges that the Software is supplied "as is" by
the Licensor without any other express or tacit warranty, other than
that provided for in Article 9.2 <#good-faith> and, in particular,
without any warranty as to its commercial value, its secured, safe,
innovative or relevant nature.
Specifically, the Licensor does not warrant that the Software is free
from any error, that it will operate without interruption, that it will
be compatible with the Licensee's own equipment and software
configuration, nor that it will meet the Licensee's requirements.
9.4 The Licensor does not either expressly or tacitly warrant that the
Software does not infringe any third party intellectual property right
relating to a patent, software or any other property right. Therefore,
the Licensor disclaims any and all liability towards the Licensee
arising out of any or all proceedings for infringement that may be
instituted in respect of the use, modification and redistribution of the
Software. Nevertheless, should such proceedings be instituted against
the Licensee, the Licensor shall provide it with technical and legal
expertise for its defense. Such technical and legal expertise shall be
decided on a case-by-case basis between the relevant Licensor and the
Licensee pursuant to a memorandum of understanding. The Licensor
disclaims any and all liability as regards the Licensee's use of the
name of the Software. No warranty is given as regards the existence of
prior rights over the name of the Software or as regards the existence
of a trademark.
Article 10 - TERMINATION
10.1 In the event of a breach by the Licensee of its obligations
hereunder, the Licensor may automatically terminate this Agreement
thirty (30) days after notice has been sent to the Licensee and has
remained ineffective.
10.2 A Licensee whose Agreement is terminated shall no longer be
authorized to use, modify or distribute the Software. However, any
licenses that it may have granted prior to termination of the Agreement
shall remain valid subject to their having been granted in compliance
with the terms and conditions hereof.
Article 11 - MISCELLANEOUS
11.1 EXCUSABLE EVENTS
Neither Party shall be liable for any or all delay, or failure to
perform the Agreement, that may be attributable to an event of force
majeure, an act of God or an outside cause, such as defective
functioning or interruptions of the electricity or telecommunications
networks, network paralysis following a virus attack, intervention by
government authorities, natural disasters, water damage, earthquakes,
fire, explosions, strikes and labor unrest, war, etc.
11.2 Any failure by either Party, on one or more occasions, to invoke
one or more of the provisions hereof, shall under no circumstances be
interpreted as being a waiver by the interested Party of its right to
invoke said provision(s) subsequently.
11.3 The Agreement cancels and replaces any or all previous agreements,
whether written or oral, between the Parties and having the same
purpose, and constitutes the entirety of the agreement between said
Parties concerning said purpose. No supplement or modification to the
terms and conditions hereof shall be effective as between the Parties
unless it is made in writing and signed by their duly authorized
representatives.
11.4 In the event that one or more of the provisions hereof were to
conflict with a current or future applicable act or legislative text,
said act or legislative text shall prevail, and the Parties shall make
the necessary amendments so as to comply with said act or legislative
text. All other provisions shall remain effective. Similarly, invalidity
of a provision of the Agreement, for any reason whatsoever, shall not
cause the Agreement as a whole to be invalid.
11.5 LANGUAGE
The Agreement is drafted in both French and English and both versions
are deemed authentic.
Article 12 - NEW VERSIONS OF THE AGREEMENT
12.1 Any person is authorized to duplicate and distribute copies of this
Agreement.
12.2 So as to ensure coherence, the wording of this Agreement is
protected and may only be modified by the authors of the License, who
reserve the right to periodically publish updates or new versions of the
Agreement, each with a separate number. These subsequent versions may
address new issues encountered by Free Software.
12.3 Any Software distributed under a given version of the Agreement may
only be subsequently distributed under the same version of the Agreement
or a subsequent version, subject to the provisions of Article 5.3.4
<#compatibility>.
Article 13 - GOVERNING LAW AND JURISDICTION
13.1 The Agreement is governed by French law. The Parties agree to
endeavor to seek an amicable solution to any disagreements or disputes
that may arise during the performance of the Agreement.
13.2 Failing an amicable solution within two (2) months as from their
occurrence, and unless emergency proceedings are necessary, the
disagreements or disputes shall be referred to the Paris Courts having
jurisdiction, by the more diligent Party.
GNU AFFERO GENERAL PUBLIC LICENSE
Version 3, 19 November 2007
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
Preamble
The GNU Affero General Public License is a free, copyleft license for software and other kinds of works, specifically designed to ensure cooperation with the community in the case of network server software.
The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, our General Public Licenses are intended to guarantee your freedom to share and change all versions of a program--to make sure it remains free software for all its users.
When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for them if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs, and that you know you can do these things.
Developers that use our General Public Licenses protect your rights with two steps: (1) assert copyright on the software, and (2) offer you this License which gives you legal permission to copy, distribute and/or modify the software.
A secondary benefit of defending all users' freedom is that improvements made in alternate versions of the program, if they receive widespread use, become available for other developers to incorporate. Many developers of free software are heartened and encouraged by the resulting cooperation. However, in the case of software used on network servers, this result may fail to come about. The GNU General Public License permits making a modified version and letting the public access it on a server without ever releasing its source code to the public.
The GNU Affero General Public License is designed specifically to ensure that, in such cases, the modified source code becomes available to the community. It requires the operator of a network server to provide the source code of the modified version running there to the users of that server. Therefore, public use of a modified version, on a publicly accessible server, gives the public access to the source code of the modified version.
An older license, called the Affero General Public License and published by Affero, was designed to accomplish similar goals. This is a different license, not a version of the Affero GPL, but Affero has released a new version of the Affero GPL which permits relicensing under this license.
The precise terms and conditions for copying, distribution and modification follow.
TERMS AND CONDITIONS
0. Definitions.
"This License" refers to version 3 of the GNU Affero General Public License.
"Copyright" also means copyright-like laws that apply to other kinds of works, such as semiconductor masks.
"The Program" refers to any copyrightable work licensed under this License. Each licensee is addressed as "you". "Licensees" and "recipients" may be individuals or organizations.
To "modify" a work means to copy from or adapt all or part of the work in a fashion requiring copyright permission, other than the making of an exact copy. The resulting work is called a "modified version" of the earlier work or a work "based on" the earlier work.
A "covered work" means either the unmodified Program or a work based on the Program.
To "propagate" a work means to do anything with it that, without permission, would make you directly or secondarily liable for infringement under applicable copyright law, except executing it on a computer or modifying a private copy. Propagation includes copying, distribution (with or without modification), making available to the public, and in some countries other activities as well.
To "convey" a work means any kind of propagation that enables other parties to make or receive copies. Mere interaction with a user through a computer network, with no transfer of a copy, is not conveying.
An interactive user interface displays "Appropriate Legal Notices" to the extent that it includes a convenient and prominently visible feature that (1) displays an appropriate copyright notice, and (2) tells the user that there is no warranty for the work (except to the extent that warranties are provided), that licensees may convey the work under this License, and how to view a copy of this License. If the interface presents a list of user commands or options, such as a menu, a prominent item in the list meets this criterion.
1. Source Code.
The "source code" for a work means the preferred form of the work for making modifications to it. "Object code" means any non-source form of a work.
A "Standard Interface" means an interface that either is an official standard defined by a recognized standards body, or, in the case of interfaces specified for a particular programming language, one that is widely used among developers working in that language.
The "System Libraries" of an executable work include anything, other than the work as a whole, that (a) is included in the normal form of packaging a Major Component, but which is not part of that Major Component, and (b) serves only to enable use of the work with that Major Component, or to implement a Standard Interface for which an implementation is available to the public in source code form. A "Major Component", in this context, means a major essential component (kernel, window system, and so on) of the specific operating system (if any) on which the executable work runs, or a compiler used to produce the work, or an object code interpreter used to run it.
The "Corresponding Source" for a work in object code form means all the source code needed to generate, install, and (for an executable work) run the object code and to modify the work, including scripts to control those activities. However, it does not include the work's System Libraries, or general-purpose tools or generally available free programs which are used unmodified in performing those activities but which are not part of the work. For example, Corresponding Source includes interface definition files associated with source files for the work, and the source code for shared libraries and dynamically linked subprograms that the work is specifically designed to require, such as by intimate data communication or control flow between those
subprograms and other parts of the work.
The Corresponding Source need not include anything that users can regenerate automatically from other parts of the Corresponding Source.
The Corresponding Source for a work in source code form is that same work.
2. Basic Permissions.
All rights granted under this License are granted for the term of copyright on the Program, and are irrevocable provided the stated conditions are met. This License explicitly affirms your unlimited permission to run the unmodified Program. The output from running a covered work is covered by this License only if the output, given its content, constitutes a covered work. This License acknowledges your rights of fair use or other equivalent, as provided by copyright law.
You may make, run and propagate covered works that you do not convey, without conditions so long as your license otherwise remains in force. You may convey covered works to others for the sole purpose of having them make modifications exclusively for you, or provide you with facilities for running those works, provided that you comply with the terms of this License in conveying all material for which you do not control copyright. Those thus making or running the covered works for you must do so exclusively on your behalf, under your direction and control, on terms that prohibit them from making any copies of your copyrighted material outside their relationship with you.
Conveying under any other circumstances is permitted solely under the conditions stated below. Sublicensing is not allowed; section 10 makes it unnecessary.
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
No covered work shall be deemed part of an effective technological measure under any applicable law fulfilling obligations under article 11 of the WIPO copyright treaty adopted on 20 December 1996, or similar laws prohibiting or restricting circumvention of such measures.
When you convey a covered work, you waive any legal power to forbid circumvention of technological measures to the extent such circumvention is effected by exercising rights under this License with respect to the covered work, and you disclaim any intention to limit operation or modification of the work as a means of enforcing, against the work's users, your or third parties' legal rights to forbid circumvention of technological measures.
4. Conveying Verbatim Copies.
You may convey verbatim copies of the Program's source code as you receive it, in any medium, provided that you conspicuously and appropriately publish on each copy an appropriate copyright notice; keep intact all notices stating that this License and any non-permissive terms added in accord with section 7 apply to the code; keep intact all notices of the absence of any warranty; and give all recipients a copy of this License along with the Program.
You may charge any price or no price for each copy that you convey, and you may offer support or warranty protection for a fee.
5. Conveying Modified Source Versions.
You may convey a work based on the Program, or the modifications to produce it from the Program, in the form of source code under the terms of section 4, provided that you also meet all of these conditions:
a) The work must carry prominent notices stating that you modified it, and giving a relevant date.
b) The work must carry prominent notices stating that it is released under this License and any conditions added under section 7. This requirement modifies the requirement in section 4 to "keep intact all notices".
c) You must license the entire work, as a whole, under this License to anyone who comes into possession of a copy. This License will therefore apply, along with any applicable section 7 additional terms, to the whole of the work, and all its parts, regardless of how they are packaged. This License gives no permission to license the work in any other way, but it does not invalidate such permission if you have separately received it.
d) If the work has interactive user interfaces, each must display Appropriate Legal Notices; however, if the Program has interactive interfaces that do not display Appropriate Legal Notices, your work need not make them do so.
A compilation of a covered work with other separate and independent works, which are not by their nature extensions of the covered work, and which are not combined with it such as to form a larger program, in or on a volume of a storage or distribution medium, is called an "aggregate" if the compilation and its resulting copyright are not used to limit the access or legal rights of the compilation's users beyond what the individual works permit. Inclusion of a covered work in an aggregate does not cause this License to apply to the other parts of the aggregate.
6. Conveying Non-Source Forms.
You may convey a covered work in object code form under the terms of sections 4 and 5, provided that you also convey the machine-readable Corresponding Source under the terms of this License, in one of these ways:
a) Convey the object code in, or embodied in, a physical product (including a physical distribution medium), accompanied by the Corresponding Source fixed on a durable physical medium customarily used for software interchange.
b) Convey the object code in, or embodied in, a physical product (including a physical distribution medium), accompanied by a written offer, valid for at least three years and valid for as long as you offer spare parts or customer support for that product model, to give anyone who possesses the object code either (1) a copy of the Corresponding Source for all the software in the product that is covered by this License, on a durable physical medium customarily used for software interchange, for a price no more than your reasonable cost of physically performing this conveying of source, or (2) access to copy the Corresponding Source from a network server at no charge.
c) Convey individual copies of the object code with a copy of the written offer to provide the Corresponding Source. This alternative is allowed only occasionally and noncommercially, and only if you received the object code with such an offer, in accord with subsection 6b.
d) Convey the object code by offering access from a designated place (gratis or for a charge), and offer equivalent access to the Corresponding Source in the same way through the same place at no further charge. You need not require recipients to copy the Corresponding Source along with the object code. If the place to copy the object code is a network server, the Corresponding Source may be on a different server (operated by you or a third party) that supports equivalent copying facilities, provided you maintain clear directions next to the object code saying where to find the Corresponding Source. Regardless of what server hosts the Corresponding Source, you remain obligated to ensure that it is available for as long as needed to satisfy these requirements.
e) Convey the object code using peer-to-peer transmission, provided you inform other peers where the object code and Corresponding Source of the work are being offered to the general public at no charge under subsection 6d.
A separable portion of the object code, whose source code is excluded from the Corresponding Source as a System Library, need not be included in conveying the object code work.
A "User Product" is either (1) a "consumer product", which means any tangible personal property which is normally used for personal, family, or household purposes, or (2) anything designed or sold for incorporation into a dwelling. In determining whether a product is a consumer product, doubtful cases shall be resolved in favor of coverage. For a particular product received by a particular user, "normally used" refers to a typical or common use of that class of product, regardless of the status of the particular user or of the way in which the particular user actually uses, or expects or is expected to use, the product. A product is a consumer product regardless of whether the product has substantial commercial, industrial or non-consumer uses, unless such uses represent the only significant mode of use of the product.
"Installation Information" for a User Product means any methods, procedures, authorization keys, or other information required to install and execute modified versions of a covered work in that User Product from a modified version of its Corresponding Source. The information must suffice to ensure that the continued functioning of the modified object code is in no case prevented or interfered with solely because modification has been made.
If you convey an object code work under this section in, or with, or specifically for use in, a User Product, and the conveying occurs as part of a transaction in which the right of possession and use of the User Product is transferred to the recipient in perpetuity or for a fixed term (regardless of how the transaction is characterized), the Corresponding Source conveyed under this section must be accompanied by the Installation Information. But this requirement does not apply if neither you nor any third party retains the ability to install modified object code on the User Product (for example, the work has been installed in ROM).
The requirement to provide Installation Information does not include a requirement to continue to provide support service, warranty, or updates for a work that has been modified or installed by the recipient, or for the User Product in which it has been modified or installed. Access to a network may be denied when the modification itself materially and adversely affects the operation of the network or violates the rules and protocols for communication across the network.
Corresponding Source conveyed, and Installation Information provided, in accord with this section must be in a format that is publicly documented (and with an implementation available to the public in source code form), and must require no special password or key for unpacking, reading or copying.
7. Additional Terms.
"Additional permissions" are terms that supplement the terms of this License by making exceptions from one or more of its conditions. Additional permissions that are applicable to the entire Program shall be treated as though they were included in this License, to the extent that they are valid under applicable law. If additional permissions apply only to part of the Program, that part may be used separately under those permissions, but the entire Program remains governed by this License without regard to the additional permissions.
When you convey a copy of a covered work, you may at your option remove any additional permissions from that copy, or from any part of it. (Additional permissions may be written to require their own removal in certain cases when you modify the work.) You may place additional permissions on material, added by you to a covered work, for which you have or can give appropriate copyright permission.
Notwithstanding any other provision of this License, for material you add to a covered work, you may (if authorized by the copyright holders of that material) supplement the terms of this License with terms:
a) Disclaiming warranty or limiting liability differently from the terms of sections 15 and 16 of this License; or
b) Requiring preservation of specified reasonable legal notices or author attributions in that material or in the Appropriate Legal Notices displayed by works containing it; or
c) Prohibiting misrepresentation of the origin of that material, or requiring that modified versions of such material be marked in reasonable ways as different from the original version; or
d) Limiting the use for publicity purposes of names of licensors or authors of the material; or
e) Declining to grant rights under trademark law for use of some trade names, trademarks, or service marks; or
f) Requiring indemnification of licensors and authors of that material by anyone who conveys the material (or modified versions of it) with contractual assumptions of liability to the recipient, for any liability that these contractual assumptions directly impose on those licensors and authors.
All other non-permissive additional terms are considered "further restrictions" within the meaning of section 10. If the Program as you received it, or any part of it, contains a notice stating that it is governed by this License along with a term that is a further restriction, you may remove that term. If a license document contains a further restriction but permits relicensing or conveying under this License, you may add to a covered work material governed by the terms of that license document, provided that the further restriction does not survive such relicensing or conveying.
If you add terms to a covered work in accord with this section, you must place, in the relevant source files, a statement of the additional terms that apply to those files, or a notice indicating where to find the applicable terms.
Additional terms, permissive or non-permissive, may be stated in the form of a separately written license, or stated as exceptions; the above requirements apply either way.
8. Termination.
You may not propagate or modify a covered work except as expressly provided under this License. Any attempt otherwise to propagate or modify it is void, and will automatically terminate your rights under this License (including any patent licenses granted under the third paragraph of section 11).
However, if you cease all violation of this License, then your license from a particular copyright holder is reinstated (a) provisionally, unless and until the copyright holder explicitly and finally terminates your license, and (b) permanently, if the copyright holder fails to notify you of the violation by some reasonable means prior to 60 days after the cessation.
Moreover, your license from a particular copyright holder is reinstated permanently if the copyright holder notifies you of the violation by some reasonable means, this is the first time you have received notice of violation of this License (for any work) from that copyright holder, and you cure the violation prior to 30 days after your receipt of the notice.
Termination of your rights under this section does not terminate the licenses of parties who have received copies or rights from you under this License. If your rights have been terminated and not permanently reinstated, you do not qualify to receive new licenses for the same material under section 10.
9. Acceptance Not Required for Having Copies.
You are not required to accept this License in order to receive or run a copy of the Program. Ancillary propagation of a covered work occurring solely as a consequence of using peer-to-peer transmission to receive a copy likewise does not require acceptance. However, nothing other than this License grants you permission to propagate or modify any covered work. These actions infringe copyright if you do not accept this License. Therefore, by modifying or propagating a covered work, you indicate your acceptance of this License to do so.
10. Automatic Licensing of Downstream Recipients.
Each time you convey a covered work, the recipient automatically receives a license from the original licensors, to run, modify and propagate that work, subject to this License. You are not responsible for enforcing compliance by third parties with this License.
An "entity transaction" is a transaction transferring control of an organization, or substantially all assets of one, or subdividing an organization, or merging organizations. If propagation of a covered work results from an entity transaction, each party to that transaction who receives a copy of the work also receives whatever licenses to the work the party's predecessor in interest had or could give under the previous paragraph, plus a right to possession of the Corresponding Source of the work from the predecessor in interest, if the predecessor has it or can get it with reasonable efforts.
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11. Patents.
A "contributor" is a copyright holder who authorizes use under this License of the Program or a work on which the Program is based. The work thus licensed is called the contributor's "contributor version".
A contributor's "essential patent claims" are all patent claims owned or controlled by the contributor, whether already acquired or hereafter acquired, that would be infringed by some manner, permitted by this License, of making, using, or selling its contributor version, but do not include claims that would be infringed only as a consequence of further modification of the contributor version. For purposes of this definition, "control" includes the right to grant patent sublicenses in a manner consistent with the requirements of this License.
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In the following three paragraphs, a "patent license" is any express agreement or commitment, however denominated, not to enforce a patent (such as an express permission to practice a patent or covenant not to sue for patent infringement). To "grant" such a patent license to a party means to make such an agreement or commitment not to enforce a patent against the party.
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license to downstream recipients. "Knowingly relying" means you have actual knowledge that, but for the patent license, your conveying the covered work in a country, or your recipient's use of the covered work in a country, would infringe one or more identifiable patents in that country that you have reason to believe are valid.
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If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may
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If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If your software can interact with users remotely through a computer network, you should also make sure that it provides a way for users to get its source. For example, if your program is a web application, its interface could display a "Source" link that leads users to an archive of the code. There are many ways you could offer source, and different solutions will be better for different programs; see section 13 for the specific requirements.
You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see <http://www.gnu.org/licenses/>.
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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.
To get the last commits from this repository into your fork use the following commands:
```sh
git remote add upstream https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow.git
git pull upstream master
```
## 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.
### Prerequisites
To run nextflow on you 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.
```sh
docker run hello-world
```
### Installing
To install nextflow on you computer simply run the following command:
## Getting the last updates
```sh
src/install_nextflow.sh
```
Then to initialise a given tools run the following command:
To get the last commits from this repository into your fork use the following commands:
For the first time:
```sh
src/docker_modules/<tool_name>/<tool_version>/docker_init.sh
git remote add upstream git@gitbio.ens-lyon.fr:LBMC/nextflow.git
git pull upstream master
```
for example to initialise `file_handle` version `0.1.1`, run:
Then to make an update:
```sh
src/docker_modules/file_handle/0.1.1/docker_init.sh
git pull upstream master
git merge upstream/master
```
To initialise all the tools:
```sh
find src/docker_modules/ -name "docker_init.sh" | awk '{system($0)}'
```
## Getting Started
## Running the tests
These instructions will get you a copy of the project as a template when you want to build your own 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
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
cd ..
```
[you can follow them here.](doc/getting_started.md)
Then to run the tests for a given tools run the following command:
## Building your pipeline
```sh
src/nf_modules/<tool_name>/<tool_version>/tests/tests.sh
```
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.
for example to run the tests on `Bowtie2` run:
## Existing Nextflow pipeline
```sh
src/nf_modules/Bowtie2/tests/tests.sh
```
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
This project is licensed under the CeCiLL License- see the [LICENSE](LICENSE) file for details
# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
#
# SPDX-License-Identifier: AGPL-3.0-or-later
*
# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
#
# SPDX-License-Identifier: AGPL-3.0-or-later
*
# SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
#
# SPDX-License-Identifier: AGPL-3.0-or-later
*.pdf
all: TP_experimental_biologists.pdf TP_computational_biologists.pdf
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")'
---
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 866 Jun 18 17:13 kallisto.config
-rw-r--r-- 1 laurent users 2711 Jun 18 17:13 kallisto.nf
drwxr-xr-x 2 laurent users 4096 Jun 18 17:14 tests/
src/nf_modules/Kallisto/tests:
total 16
-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 [`kallisto.config`](./src/nf_modules/Kallisto/kallisto.config) file contains instructions for two profiles : `sge` and `docker`.
The [`kallisto.nf`](./src/nf_modules/Kallisto/kallisto.nf) 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 [`tests/`](./src/nf_modules/kallisto/tests/) folder. Those tests correspond to execution of the processes present in the [`kallisto.nf`](./src/nf_modules/Kallisto/kallisto.nf) file 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/kallisto.config)
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 `sge` and `docker` profile.
```Groovy
profiles {
docker {
docker.temp = 'auto'
docker.enabled = true
process {
}
}
sge {
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 {
$index_fasta {
container = "kallisto:0.44.0"
}
$mapping_fastq {
container = "kallisto:0.44.0"
}
}
```
### `sge` profile
The `sge` 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{
$index_fasta {
beforeScript = "module purge; module load Kallisto/0.44.0"
executor = "sge"
cpus = 1
memory = "5GB"
time = "6h"
queueSize = 1000
pollInterval = '60sec'
queue = 'h6-E5-2667v4deb128'
penv = 'openmp8'
}
$mapping_fastq {
beforeScript = "module purge; module load Kallisto/0.44.0"
executor = "sge"
cpus = 4
memory = "5GB"
time = "6h"
queueSize = 1000
pollInterval = '60sec'
queue = 'h6-E5-2667v4deb128'
penv = 'openmp8'
}
}
```
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/)
---
title: "TP for experimental biologists"
author: Laurent Modolo [laurent.modolo@ens-lyon.fr](mailto:laurent.modolo@ens-lyon.fr)
date: 6 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 build your own pipeline with nextflow and using the tools already *wrapped*.
For this we are going to build a small RNASeq analysis pipeline that should run the following steps:
- remove Illumina adaptors
- trim reads by quality
- build the index of a reference genome
- estimate the amount of RNA fragments mapping to the transcripts of this genome
# 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 [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow) as a template.
To easily do so, go to the [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow) repository and click on the [**fork**](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/forks/new) button.
![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. You can then write modifications in your project, and if they are of interest for the source repository (here [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow)) create a merge request. Merge requests are sent to the source repository to ask the maintainers to integrate modifications.
![merge request button](img/merge_request.png)
## Project organisation
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 [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow). You can explore this project, all the code in it is under the CeCILL licence (in the [LICENCE](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/LICENSE) file).
The [README.md](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/README.md) file contains instructions to run your pipeline and test its installation.
The [CONTRIBUTING.md](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/CONTRIBUTING.md) file contains guidelines to follow if you want to contribute to the [pipelines/nextflow](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow) (making a merge request for example).
The [data](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/tree/master/data) folder will be the place where you store the raw data for your analysis.
The [results](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/tree/master/results) folder will be the place where you store the results of your analysis.
Note that the content of these two folders should never be saved on git.
The [doc](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/tree/master/doc) folder contains the documentation of this practical course.
And most interestingly for you, the [src](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/tree/master/src) contains code to wrap tools. This folder contains two subdirectories. A `docker_modules`, a `nf_modules` and a `sge_modules` folder.
### `docker_modules`
The `src/docker_modules` contains the code to wrap tools in [Docker](https://www.docker.com/what-docker). [Docker](https://www.docker.com/what-docker) is a framework that allows you to execute software within [containers](https://www.docker.com/what-container). The `docker_modules` contains directory corresponding to tools and subdirectories corresponding to their version.
```sh
ls -l src/docker_modules/
rwxr-xr-x 3 laurent _lpoperator 96 May 25 15:42 BEDtools/
drwxr-xr-x 4 laurent _lpoperator 128 Jun 5 16:14 Bowtie2/
drwxr-xr-x 3 laurent _lpoperator 96 May 25 15:42 FastQC/
drwxr-xr-x 4 laurent _lpoperator 128 Jun 5 16:14 HTSeq/
```
To each `tools/version` corresponds two files:
```sh
ls -l src/docker_modules/Bowtie2/2.3.4.1/
-rw-r--r-- 1 laurent _lpoperator 283 Jun 5 15:07 Dockerfile
-rwxr-xr-x 1 laurent _lpoperator 79 Jun 5 16:18 docker_init.sh*
```
The `Dockerfile` is the [Docker](https://www.docker.com/what-docker) recipe to create a [container](https://www.docker.com/what-container) containing `Bowtie2` in its `2.3.4.1` version. And the `docker_init.sh` file is a small script to create the [container](https://www.docker.com/what-container) from this recipe.
By running this script you will be able to easily install tools in different versions on your personal computer and use it in your pipeline. Some of the advantages are:
- Whatever the computer, the installation and the results will be the same
- You can keep [container](https://www.docker.com/what-container) for old version of tools and run it on new systems (science = reproducibility)
- You don’t have to bother with tedious installation procedures, somebody else already did the job and wrote a `Dockerfile`.
- You can easily keep [containers](https://www.docker.com/what-container) for different version of the same tools.
### `sge_modules`
The `src/sge_modules` folder is not really there. It’s a submodule of the project [PSMN/modules](https://gitlab.biologie.ens-lyon.fr/PSMN/modules). To populate it locally you can use the following command:
```sh
git submodule init
```
Like the `src/docker_modules` the [PSMN/modules](https://gitlab.biologie.ens-lyon.fr/PSMN/modules) project describe recipes to install tools and use them. The main difference is that you cannot use [Docker](https://www.docker.com/what-docker) on the PSMN. Instead you have to use another framework [Environment Module](http://www.ens-lyon.fr/PSMN/doku.php?id=documentation:tools:modules) which allows you to load modules for specific tools and version.
The [README.md](https://gitlab.biologie.ens-lyon.fr/PSMN/modules/blob/master/README.md) file of the [PSMN/modules](https://gitlab.biologie.ens-lyon.fr/PSMN/modules) repository contains all the instruction to be able to load the modules maintained by the LBMC and present in the [PSMN/modules](https://gitlab.biologie.ens-lyon.fr/PSMN/modules) repository.
### `nf_modules`
The `src/nf_modules` folder contains templates of [nextflow](https://www.nextflow.io/) wrappers for the tools available in [Docker](https://www.docker.com/what-docker) and [SGE](http://www.ens-lyon.fr/PSMN/doku.php?id=documentation:tools:sge). The details of the [nextflow](https://www.nextflow.io/) wrapper will be presented in the next section. Alongside the `.nf` and `.config` there is a `tests` folder that contains a `tests.sh` script to run test on the tool.
# Nextflow pipeline
A pipeline is a succession of **process**. Each process has data input(s) and optional data output(s). Data flows are modeled as **channels**.
## Processes
Here is an example of **process**:
```Groovy
process sample_fasta {
input:
file fasta from fasta_file
output:
file "sample.fasta" into fasta_sample
script:
"""
head ${fasta} > sample.fasta
"""
}
```
We have the process `sample_fasta` that takes as `fasta_file` channel as input and output a `fasta_sample` channel. The process itself is defined in the `script:` block and within `"""`.
```Groovy
input:
file fasta from fasta_file
```
When we zoom on the `input:` block we see that we define a variable `fasta` of type `file` from the `fasta_file` channel. This mean that groovy 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:
file "sample.fasta" into 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 send into the pipeline `fasta_sample`
Using the WebIDE of Gitlab, create a file `src/fasta_sampler.nf` with this process and commit to your repository.
![webide](img/webide.png)
## Channels
Why bother with channels? In the above example, the advantages of channels are not really clear. We could have just given the `fasta` file to the process. 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 channels.
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/fasta/` into the process that take it as input.
Add the definition of the channel to the `src/fasta_sampler.nf` file and commit 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. To easily do that set the visibility level to *public* in the settings/General/Permissions page of your project.
You can then run the following commands to download your project on your computer:
```sh
git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/<usr_name>/nextflow.git
cd nextflow
src/install_nextflow.sh
```
We also need data to run our pipeline:
```
cd data
git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/LBMC/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 nextflow would 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:
file "*_sample.fasta" into fasta_sample
script:
"""
head ${fasta} > ${fasta.baseName}_sample.fasta
"""
```
Add this to your `src/fasta_sampler.nf` file with the WebIDE and commit to your repository before pulling your modifications locally.
You can run your pipeline again and check the content of the folder `results/sampling`.
# 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.
## Create your Docker containers
For this practical, we are going to need the following tools:
- For Illumina adaptor removal: cutadapt
- For reads trimming by quality: UrQt
- For mapping and quantifying reads: BEDtools and Kallisto
To initialize these tools, follow the **Installing** section of the [README.md](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/README.md) file.
If you are using a CBP computer don’t forget to clean up your docker containers at the end of the practical with the following command:
```sh
docker rm $(docker stop $(docker ps -aq))
docker rmi $(docker images -qf "dangling=true")
```
## Cutadapt
The first step of the pipeline is to remove any Illumina adaptor left in your read files.
Open the WebIDE and create a `src/RNASeq.nf` file. Browse for [src/nf_modules/cutadapt/cutadapt.nf](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/cutadapt/cutadapt.nf), this file contains examples for cutadapt. We are interested in the *Illumina adaptor removal*, *for paired-end data* section of the code. Copy this code in your pipeline and commit.
Compared to before, we have few new lines:
```Groovy
params.fastq = "$baseDir/data/fastq/*_{1,2}.fastq"
```
We declare a variable that contain the path of the fastq file to look for. The advantage of using `params.fastq` is that now the option `--fastq` in our call to the pipeline allows us to define this variable:
```sh
./nextflow src/RNASeq.nf --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq"
```
```Groovy
log.info "fastq files: ${params.fastq}"
```
This line simply displays the value of the variable
```Groovy
Channel
.fromFilePairs( params.fastq )
```
As we are working with paired-end RNASeq data, we tell nextflow to send pairs of fastq in the `fastq_file` channel.
### cutadapt.config
For the `fastq_sampler.nf` pipeline we used the command `head` present in most base UNIX systems. Here we want to use `cutadapt` which is not. Therefore, we have three main options:
- install cutadapt locally so nextflow can use it
- launch the process in a Docker container that has cutadapt installed
- launch the process with SGE while loading the correct module to have cutadapt available
We are not going to use the first option which requires no configuration for nextflow but tedious tools installations. Instead, we are going to use existing *wrappers* and tell nextflow about it. This is what the [src/nf_modules/cutadapt/cutadapt.config](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/cutadapt/cutadapt.config) is used for.
Copy the content of this config file to an `src/RNASeq.config` file. This file is structured in process blocks. Here we are only interested in configuring `adaptor_removal` process not `trimming` process. So you can remove the `trimming` block and commit.
You can test your pipeline with the following command:
```sh
./nextflow src/RNASeq.nf -c src/RNASeq.config -profile docker --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq"
```
## UrQt
The second step of the pipeline is to trim reads by quality.
Browse for [src/nf_modules/UrQt/urqt.nf](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/UrQt/urqt.nf), this file contains examples for UrQt. We are interested in the *for paired-end data* section of the code. Copy the process section code in your pipeline and commit.
This code won’t work if you try to run it: the `fastq_file` channel is already consumed by the `adaptor_removal` process. In nextflow once a channel is used by a process, it ceases to exist. Moreover, we don’t want to trim the input fastq, we want to trim the fastq that comes from the `adaptor_removal` process.
Therefore, you need to change the line:
```Groovy
set pair_id, file(reads) from fastq_files
```
In the `trimming` process to:
```Groovy
set pair_id, file(reads) from fastq_files_cut
```
The two processes are now connected by the channel `fastq_files_cut`.
Add the content of the [src/nf_modules/UrQt/urqt.config](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/UrQt/urqt.config) file to your `src/RNASeq.config` file and commit.
You can test your pipeline.
## BEDtools
Kallisto 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` annotation `data/tiny_dataset/annot/tiny.bed`.
You can copy to your `src/RNASeq.nf` file the content of [src/nf_modules/BEDtools/bedtools.nf](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/BEDtools/bedtools.nf) and to your `src/RNASeq.config` file the content of [src/nf_modules/BEDtools/bedtools.config](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/BEDtools/bedtools.config).
Commit your work and test your pipeline with the following command:
```sh
./nextflow src/RNASeq.nf -c src/RNASeq.config -profile docker --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 on this index.
You can copy to your `src/RNASeq.nf` file the relevant content of [src/nf_modules/Kallisto/kallisto.nf](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/Kallisto/kallisto.nf) and to your `src/RNASeq.config` file the content of [src/nf_modules/Kallisto/kallisto.config](https://gitlab.biologie.ens-lyon.fr/pipelines/nextflow/blob/master/src/nf_modules/Kallisto/kallisto.config).
We are going to work with paired-end so only copy the relevant processes. The `index_fasta` process needs to take as input the output of your `fasta_from_bed` process. The `fastq` input of your `mapping_fastq` process needs to take as input the output of your `index_fasta` process and the `trimming` process.
Commit your work and test your pipeline.
You now have a RNASeq analysis pipeline that can run locally with Docker!
## Additional nextflow option
With nextflow you can restart the computation of a pipeline and get a trace of the process with the following options:
```sh
-resume -with-dag results/RNASeq_dag.pdf -with-timeline results/RNASeq_timeline
```
# 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@e5-2667v4comp1
```
## Set your environment
Make the LBMC modules available to you:
```sh
ln -s /Xnfs/lbmcdb/common/modules/modulefiles ~/privatemodules
echo "module use ~/privatemodules" >> .bashrc
```
Then you need to clone your pipeline and get the data:
```sh
git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/lmodolo/nextflow.git
cd nextflow/data
git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/LBMC/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 deconnection, you can restore your session with the command `tmux a`.
```sh
tmux
module load nextflow/0.28.2
nextflow src/RNASeq.nf -c src/RNASeq.config -profile sge --fastq "data/tiny_dataset/fastq/*_R{1,2}.fastq" --fasta "data/tiny_dataset/fasta/tiny_v2.fasta" --bed "data/tiny_dataset/annot/tiny.bed"
```
To use the scratch for nextflow computations add the option :
```sh
-w /scratch/login
```
You just ran your pipeline on the PSMN!
<!--
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!
<!--
SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
SPDX-License-Identifier: CC-BY-SA-4.0
-->
# Getting Started
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
```
and `git`
```sh
git --version
```
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
docker run hello-world
```
Alternatively if you are on Linux, you can use `singularity`:
```sh
singularity run docker://hello-world
```
## Installing
To install nextflow on your computer simply run the following command:
```sh
git clone git@gitbio.ens-lyon.fr:LBMC/nextflow.git
cd nextflow/
src/install_nextflow.sh
```
## Running a toy RNASeq quantification pipeline
To run tests we first need to get a training set
```sh
cd data
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
cd ..
```
Then to run the tests for a given tools run the following command:
```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
```
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
qsub src/ccin2p3.pbs
```
SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
SPDX-License-Identifier: CC-BY-SA-4.0
SPDX-FileCopyrightText: 2022 Laurent Modolo <laurent.modolo@ens-lyon.fr>
SPDX-License-Identifier: CC-BY-SA-4.0