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JSON Scatter Gather Pipeline

Let's create the Nextflow Scatter Gather pipeline with a JSON input form.

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Pay close attention to uppercase and lowercase characters when creating pipelines.

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.

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Nextflow files

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split.nf

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

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sort.nf

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

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merge.nf

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

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main.nf

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

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.

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Inputform files

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

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inputForm.json

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.

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onSubmit.js

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onRender.js

Click the Save button to save the changes.

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.
    """
    }
process sort {
    cpus 1
    memory '512 MB'
    
    input:
    path x
    
    output:
    path '*.sorted.tsv'
    
    """
    sort -gk1,1 $x > ${x.baseName}.sorted.tsv
    """
}
process merge {
  cpus 1
  memory '512 MB'
 
  publishDir 'out', mode: 'move'
 
  input:
  path x
 
  output:
  path 'merged.tsv'
 
  """
  cat $x > merged.tsv
  """
}
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())
}
{
  "fields": [
    {
      "id": "myinput",
      "label": "myinput",
      "type": "data",
      "dataFilter": {
        "dataType": "file",
        "dataFormat": ["TSV"]
      },
      "maxValues": 1,
      "minValues": 1
    }
  ]
}
function onSubmit(input) {
    var validationErrors = [];

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