# JSON Scatter Gather Pipeline

Let's create the [Nextflow Scatter Gather pipeline ](https://help.ica.illumina.com/tutorials/nextflow/scatter-gather-nextflow)with a JSON input form.

{% hint style="info" %}
Pay close attention to uppercase and lowercase characters when creating pipelines.
{% endhint %}

Select **Projects > your\_project > Flow > Pipelines**. From the **Pipelines** view, click the **+Create > Nextflow** **> JSON based** button to start creating a Nextflow pipeline.

In the **Details** tab, add values for the required *Code* (unique pipeline name) and *Description* fields. *Nextflow Version* and *Storage size* defaults to preassigned values.

### Nextflow files

#### split.nf

First, we present the individual processes. Select **Nextflow files > + Create** and label the file **split.nf**. Copy and paste the following definition.

```groovy
process split {
    cpus 1
    memory '512 MB'
    
    input:
    path x
    
    output:
    path("split.*.tsv")
    
    """
    split -a10 -d -l3 --numeric-suffixes=1 --additional-suffix .tsv ${x} split.
    """
    }
```

#### sort.nf

Next, select **+Create** and name the file **sort.nf**. Copy and paste the following definition.

```groovy
process sort {
    cpus 1
    memory '512 MB'
    
    input:
    path x
    
    output:
    path '*.sorted.tsv'
    
    """
    sort -gk1,1 $x > ${x.baseName}.sorted.tsv
    """
}
```

#### merge.nf

Select **+Create** again and label the file **merge.nf**. Copy and paste the following definition.

<pre class="language-groovy"><code class="lang-groovy">process merge {
  cpus 1
  memory '512 MB'
 
  publishDir 'out', mode: 'move'
 
  input:
  path x
 
  output:
<strong>  path 'merged.tsv'
</strong> 
  """
<strong>  cat $x > merged.tsv
</strong>  """
}
</code></pre>

#### main.nf

Edit the main.nf file by navigating to the **Nextflow files > main.nf** tab and copying and pasting the following definition.

```groovy
nextflow.enable.dsl=2
 
include { sort } from './sort.nf'
include { split } from './split.nf'
include { merge } from './merge.nf'
 
params.myinput = "test.test"
 
workflow {
    input_ch = Channel.fromPath(params.myinput)
    split(input_ch)
    sort(split.out.flatten())
    merge(sort.out.collect())
}
```

Here, the operators *flatten* and *collect* are used to transform the emitting channels. The *Flatten* operator transforms a channel in such a way that every item of type Collection or Array is flattened so that each single entry is emitted separately by the resulting channel. The collect operator collects all the items emitted by a channel to a List and return the resulting object as a sole emission.

### Inputform files

On the Inputform files tab, edit the inputForm.json to allow selection of a file.

#### inputForm.json

```json
{
  "fields": [
    {
      "id": "myinput",
      "label": "myinput",
      "type": "data",
      "dataFilter": {
        "dataType": "file",
        "dataFormat": ["TSV"]
      },
      "maxValues": 1,
      "minValues": 1
    }
  ]
}
```

Click the Simulate button (at the bottom of the text editor) to preview the launch form fields.

The onSubmit.js and onRender.js can remain with their default scripts and are just shown here for reference.

#### onSubmit.js

```json
function onSubmit(input) {
    var validationErrors = [];

    return {
        'settings': input.settings,
        'validationErrors': validationErrors
    };
}
```

#### onRender.js

```json
function onRender(input) {

    var validationErrors = [];
    var validationWarnings = [];

    if (input.currentAnalysisSettings === null) {
        //null first time, to use it in the remainder of he javascript
        input.currentAnalysisSettings = input.analysisSettings;
    }

    switch(input.context) {
        case 'Initial': {
            renderInitial(input, validationErrors, validationWarnings);
            break;
        }
        case 'FieldChanged': {
            renderFieldChanged(input, validationErrors, validationWarnings);
            break;
        }
        case 'Edited': {
            renderEdited(input, validationErrors, validationWarnings);
            break;
        }
        default:
            return {};
    }

    return {
        'analysisSettings': input.currentAnalysisSettings,
        'settingValues': input.settingValues,
        'validationErrors': validationErrors,
        'validationWarnings': validationWarnings
    };
}

function renderInitial(input, validationErrors, validationWarnings) {
}

function renderEdited(input, validationErrors, validationWarnings) {
}

function renderFieldChanged(input, validationErrors, validationWarnings) {
}

function findField(input, fieldId){
    var fields = input.currentAnalysisSettings['fields'];
    for (var i = 0; i < fields.length; i++){
        if (fields[i].id === fieldId) {
            return fields[i];
        }
    }
    return null;
}
```

Click the `Save` button to save the changes.