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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.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: ...

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

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

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# 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

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# Contributing

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 )

```

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

You can the use tests on `read.size()` to define conditional `script` block:

```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}

  """

...

```

### Complex processes

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).

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.

```Groovy

params.fastp_protocol = ""

workflow fastp {

  take:

    fastq

  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

}

```

## `src/.docker_modules` guide lines

We are going to take the [`fastp`, `.docker_modules`](./src/.docker_module/fastp/0.20.1/) as an example.

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).

### `Dockerfile`

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.

This recipe should have:

- 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"]`)

### `docker_init.sh`

The [`docker_init.sh`](./src/.docker_module/fastp/0.20.1/docker_init.sh) script is a small sh script with the following content:

```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

```

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 :

- 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**)

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# nextflow pipeline

This repository is a template and a library repository to help you build nextflow pipeline.

You can fork this repository to build your own pipeline.

## Getting the last updates

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

For the first time:

```sh

git remote add upstream git@gitbio.ens-lyon.fr:LBMC/nextflow.git

git pull upstream master

```

Then to make an update:

```sh

git pull upstream master

git merge upstream/master

```

## Getting Started

These instructions will get you a copy of the project as a template when you want to build your own pipeline.

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

## Building your pipeline

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.

## Existing Nextflow pipeline

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

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://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

<!--

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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

```