main.nf

#!/usr/bin/env nextflow
/*
========================================================================================
                         LAVA
========================================================================================
 Longitudinal Analysis of Viral Alleles
 #### Homepage / Documentation
https://github.com/vpeddu/lava
----------------------------------------------------------------------------------------
*/

// Using the Nextflow DSL-2 to account for the logic flow of this workflow
nextflow.preview.dsl=2


def helpMessage() {
    log.info"""
    LAVA: Longitudinal Analysis of Viral Alleles

    Usage:

    An example command for running the pipeline is as follows:

    nextflow run FredHutch/CLOMP \\
        --PAIRED_END \\
        --HOST_FILTER_FIRST \\
        --OUTDIR output/
        
  
        --CONTROL_FASTQ The fastq reads for the first sample in
                        your longitudinal analysis [REQUIRED]

        --METADATA       Required argument: A two column csv - the first column is the
                        path to all the fastqs you wish to include in your analysis.
                        All fastqs that you want to include need to be specified in
                        this file AND be located in the folder from which you are
                        running lava. The second column is the temporal seperation
                        between the samples. This is unitless so you can input
                        passage number, days, or whatever condition your experiment
                        happens to have. [REQUIRED]
        
        --OUTDIR        Output directory [REQUIRED]
        
        --FASTA         Specify a reference fasta with the majority consensus of the
                        control fastq. This option must be used with the -g flag to
                        specify the protein annotations relative to the start of this
                        fasta. [REQUIRED IF NOT --GENBANK]

        --GFF           Specify a reference gff file with the protein annotations for
                        the reference fasta supplied with the -f flag. This option
                        must be paired with the -f flag. [REQUIRED IF NOT GENBANK]

        --GENBANK       Provide a Genbank accession number. This record will be used
                        to generate a majority consensus from the control fastq, and
                        this consensus will be annotated from the downloaded genbank
                        record as well. [REQUIRED IF NOT --FASTA + --GFF]

        --AF            pecify an allele frequency percentage to cut off 
                        - with a minimum of 1 percent - in whole numbers. default = ' '

        --NUC           Results are listed as nucleotide changes not amino acid
                        changes. Do not use with -png.

        --ALLELE_FREQ   Specify an allele frequency percentage to cut off - with a
                        minimum of 1 percent - in whole numbers.

        --PNG           Output results as a png. Do not use with -nuc.
        
        --DEDUPLICATE   Optional flag, will perform automatic removal of PCR
                        duplicates via DeDup.
    """.stripIndent()
}

/*
 * SET UP CONFIGURATION VARIABLES
 */

// Show help message
params.help = false
if (params.help){
    helpMessage()
    exit 0
}

params.OUTDIR= false


params.GENBANK = 'False'
params.GFF = 'False'
params.FASTA = 'NO_FILE'
params.DEDUPLICATE = 'false' 
params.ALLELE_FREQ = 'NO_VAL'

METADATA_FILE = file(params.METADATA)

/*
 * Import the processes used in this workflow
 */

include CreateGFF from './Modules.nf'
include Alignment_prep from './Modules.nf'
include Align_samples from './Modules.nf' 
include Pipeline_prep from './Modules.nf'
include Create_VCF from './Modules.nf'
include Ref_done from './Modules.nf'
include Extract_variants from './Modules.nf'
include Annotate_complex from './Modules.nf'
include Annotate_complex_first_passage from './Modules.nf'
include Generate_output from './Modules.nf'



CONTROL_FASTQ = file(params.CONTROL_FASTQ)
FASTA = file(params.FASTA)
 //input_read_ch = Channel


// Error handling for input flags
//if CONTROL_FASTQ not set 
if (!params.CONTROL_FASTQ){
    println("Must provide control FASTQ with --ControlFastq") 
    exit(1)
}
//if OUTDIR not set
if (params.OUTDIR == false) {
    println( "Must provide an output directory with --OUTDIR") 
    exit(1)
}
// If --GENBANK and --FASTA or --GFF are specified at the same time
if(((params.GENBANK != "False") && (params.FASTA != "NO_FILE"))){ 
    println("bruh --GENBANK cannot be used with --FASTA or --GFF")
    exit(1)
}
if(((params.GENBANK != "False") && (params.GFF != "False"))){ 
    println("bruh --GENBANK cannot be used with --FASTA or --GFF")
    exit(1)
}
// If --FASTA without --GENBANK or vice versa
if( (params.FASTA != "NO_FILE") && params.GFF == 'False'){ 
    println('--GFF needs to be specified with --FASTA')
    exit(1)
}
if( (params.GFF != "False") && params.FASTA == 'NO_FILE'){ 
    println('--FASTA needs to be specified with --GFF')
    exit(1)
}
// If no flags specified
if(params.GFF == "False" && params.FASTA == 'NO_FILE' && params.GENBANK == "False"){ 
    println('Either --GENBANK or --FASTA + --GFF are required flags')
    exit(1)
}

// Make sure OUTDIR ends with trailing slash

if (!params.OUTDIR.endsWith("/")){
   params.OUTDIR = "${params.OUTDIR}/"
}
input_read_ch = Channel
    .fromPath(METADATA_FILE)
    .splitCsv(header:false)

input_read_ch = Channel
    .fromPath(METADATA_FILE)
    .splitCsv(header:true)
    .map{ row-> tuple(file(row.Sample), (row.Passage)) }



// Run the workflow
workflow {
        //fml() 
    log.info nfcoreHeader()
        CreateGFF ( 
            params.GENBANK, 
            CONTROL_FASTQ,
            file(params.FASTA),
            file(params.GFF)
        )
        
        Alignment_prep ( 
            CreateGFF.out[0],
            CreateGFF.out[1],
            CreateGFF.out[2]
        )

        Align_samples ( 
            input_read_ch,
            Alignment_prep.out[0],
            input_read_ch.first(),
            params.DEDUPLICATE
            
        )

        Pipeline_prep ( 
            Align_samples.out[0].collect(),
            CreateGFF.out[2],
            CreateGFF.out[3],
            Alignment_prep.out[0]
        )

        Create_VCF ( 
            CreateGFF.out[3],
            Pipeline_prep.out[2],
            Align_samples.out[0],
            Alignment_prep.out[1],
            input_read_ch.first(),
            Alignment_prep.out[2]
        )

        Ref_done ( 
            input_read_ch.first(),
            params.ALLELE_FREQ,
            Create_VCF.out[0],
            CreateGFF.out[3],
            Pipeline_prep.out[3],
            Align_samples.out[1],
            METADATA_FILE
        )

        Extract_variants ( 
            input_read_ch.first(),
            Create_VCF.out[1],
            METADATA_FILE

        )

        Annotate_complex( 
            Extract_variants.out[0]
        )

        Annotate_complex_first_passage( 
            Ref_done.out[0],
        )

        Generate_output( 
            Annotate_complex_first_passage.out,
            Annotate_complex.out[0].collect(),
            Annotate_complex.out[1].collect(),
            Annotate_complex.out[2].collect(),
            Annotate_complex.out[3].collect(),
            Pipeline_prep.out[0],
            Pipeline_prep.out[1],
            Align_samples.out[2].collect(),
            Create_VCF.out[2].collect()
        )
        
    publish:
        Generate_output.out to: "${params.OUTDIR}" , mode: 'copy'
}

def nfcoreHeader() {

    return """
                       ooO
                     ooOOOo
                   oOOOOOOoooo
                 ooOOOooo  oooo
                /vvv\\
               /V V V\\ 
              /V  V  V\\          
             /         \\            oh wow  look at these alleles
            /           \\          /         /    
          /               \\   	  o          o
__       /                 \\     /-   o     /-
/\\     /                     \\  /\\  -/-    /\\
                                    /\\
 ___      _______  __   __  _______ 
|   |    |   _   ||  | |  ||   _   |
|   |    |  |_|  ||  |_|  ||  |_|  |
|   |    |       ||       ||       |
|   |___ |       ||       ||       |
|       ||   _   | |     | |   _   |
|_______||__| |__|  |___|  |__| |__| Version 2    
    """.stripIndent()
}