nextflow

How to use the emit option to pass the out for next step in nextflow


So my initial input file is an annotation file which contains the information for all the downstream process. So this is my step1.nf

nextflow.enable.dsl = 2

// Define the default annotation file
params.annotation_file = 'sample_annot.txt'

annotation_ch = Channel.fromPath(params.annotation_file)

// Define the process to parse the annotation file
process parse_annotation {
    tag "$annotation_file"
    publishDir "results/", mode: 'copy'

    input:
    path annotation_file


    output:
    path "sample.csv", emit: parsed_annotation

    script:
    """
    python3 /home/punit/temp/parse_annotation.py -f $annotation_file
    """
}

// Define the workflow
workflow {
    parse_annotation(annotation_ch)
}

Now this gives me desired output which is inside the result folder which is a .csv file.

Next step is use that generated output .csv file as input for the sample_parsing script which script is sample_parse.py which takes two argument as input, one is the .csv file which is generated in the result folder and other is the original annotation file which is given as here params.annotation_file = 'sample_annot.txt'

So far till i have managed to get the first step for the next part in the same nextflow how do i do it.

As i did it separately in other words i generated the first part and did the second in another nextflow script, but my goal is to do it together or in a single nextflow script

Will it be inside the same workflow or another one? i did see examples but it bit confusing so far, as i try to wrap my head around.

Any suggestion or help would be really appreciated

UPDATE The output i should get from the second script is this from which for downstream analysis i pass the files which have .id extension to call tools to fetch and download files .

So do i need to store them in a folder and emit? or how do i pass the argument

GSM1871919.id  GSM1871921.id  GSM1871923.id  GSM1871925.id  GSM1871927.id  GSM1871920.id  GSM1871922.id  GSM1871924.id  GSM1871926.id  GSM1871928.id 
PrefrontalCortexADEmoryADRC_VS_PrefrontalCortexControlEmoryADRC_C2.info.txt
PrefrontalCortexADEmoryADRC_VS_PrefrontalCortexControlEmoryADRC_C2.samplesheet.csv
PrefrontalCortexADKentuckyADRC_VS_PrefrontalCortexControlKentuckyADRC_C1.info.txt
PrefrontalCortexADKentuckyADRC_VS_PrefrontalCortexControlKentuckyADRC_C1.samplesheet.csv

The error I ran the suggested solution

nextflow run main_v2.nf
N E X T F L O W  ~  version 23.10.1
Launching `main_v2.nf` [hopeful_neumann] DSL2 - revision: d3a1cad6ba
Process `sample_annotation` declares 2 input channels but 1 were specified

 -- Check script 'main_v2.nf' at line: 45 or see '.nextflow.log' file for more details
[ERROR] Terminal initialization failed; falling back to unsupported
java.lang.IllegalStateException: Shutdown in progress
        at java.base/java.lang.ApplicationShutdownHooks.add(ApplicationShutdownHooks.java:66)
        at java.base/java.lang.Runtime.addShutdownHook(Runtime.java:216)
        at jline.internal.ShutdownHooks.addHook(ShutdownHooks.java:79)
        at jline.internal.ShutdownHooks.add(ShutdownHooks.java:43)
        at jline.TerminalSupport.init(TerminalSupport.java:46)
        at jline.UnixTerminal.init(UnixTerminal.java:47)
        at jline.TerminalFactory.create(TerminalFactory.java:101)
        at jline.TerminalFactory.get(TerminalFactory.java:159)
        at nextflow.trace.AnsiLogObserver.renderProcesses(AnsiLogObserver.groovy:249)
        at nextflow.trace.AnsiLogObserver.renderProgress(AnsiLogObserver.groovy:289)
        at nextflow.trace.AnsiLogObserver.render0(AnsiLogObserver.groovy:177)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.base/java.lang.reflect.Method.invoke(Method.java:568)
        at org.codehaus.groovy.reflection.CachedMethod.invoke(CachedMethod.java:107)
        at groovy.lang.MetaMethod.doMethodInvoke(MetaMethod.java:323)
        at groovy.lang.MetaClassImpl.invokeMethod(MetaClassImpl.java:1254)
        at groovy.lang.MetaClassImpl.invokeMethodClosure(MetaClassImpl.java:1042)
        at groovy.lang.MetaClassImpl.invokeMethod(MetaClassImpl.java:1128)
        at groovy.lang.MetaClassImpl.invokeMethod(MetaClassImpl.java:1030)
        at groovy.lang.Closure.call(Closure.java:427)
        at groovy.lang.Closure.call(Closure.java:406)
        at groovy.lang.Closure.run(Closure.java:498)
        at java.base/java.lang.Thread.run(Thread.java:833)

[-        ] process > parse_annotation -

Solution

  • If I understand correctly, it would be as simple as adding another process and a simple update to your workflow declaration. Thankfully, DSL2 allows queue channels to be used multiple times, so you don't need to emit it again or make duplicate channels.

    Something like this:

    nextflow.enable.dsl = 2
    
    // Define the default annotation file
    params.annotation_file = 'sample_annot.txt'
    
    annotation_ch = Channel.fromPath(params.annotation_file)
    
    // Define the process to parse the annotation file
    process parse_annotation {
        tag "$annotation_file"
        publishDir "results/parsed/", mode: 'copy'
    
        input:
        path annotation_file
    
    
        output:
        path "sample.csv", emit: parsed_annotation
    
        script:
        """
        python3 /home/punit/temp/parse_annotation.py -f $annotation_file
        """
    }
    
    process sample_annotation {
        tag "$annotation_file"
        publishDir "results/sampled/", mode: 'copy'
    
        input:
        path annotation_file
        path parsed_csv
    
        output:
        path "*.id", emit: out_sampled
    
        script:
        """
        python3 /home/punit/temp/sample_parse.py \\
          $annotation_file \\
          $parsed_csv
        """
    }
    // Define the workflow
    workflow {
        parse_annotation(annotation_ch)
        sample_annotations(annotation_ch, parse_annotations.out.parsed_annotations)
    }
    

    EDIT: Missed the original file in the input, and updated the process as per suggestions from OP.