> For the complete documentation index, see [llms.txt](https://help.connected.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.connected.illumina.com/connected-analytics/project/p-flow/pipelines-new-view/json-based-input-forms/json-scatter-gather-pipeline.md).
# JSON Scatter Gather Pipeline
Let's create the [Nextflow Scatter Gather pipeline ](/connected-analytics/tutorials/nextflow/scatter-gather-nextflow.md)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.
process merge {
cpus 1
memory '512 MB'
publishDir 'out', mode: 'move'
input:
path x
output:
path 'merged.tsv'
"""
cat $x > merged.tsv
"""
}
#### 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.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://help.connected.illumina.com/connected-analytics/project/p-flow/pipelines-new-view/json-based-input-forms/json-scatter-gather-pipeline.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.