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main.nf
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main.nf
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#!/usr/bin/env nextflow
/*
========================================================================================
nextflow-lcep
========================================================================================
https://github.com/mlf-core/nextflow-lcep
----------------------------------------------------------------------------------------
*/
params.gtex_counts_link = "http://duffel.rail.bio/recount/v2/SRP012682/counts_gene.tsv.gz"
params.gtex_metadata_link = "http://duffel.rail.bio/recount/SRP012682/SRP012682.tsv"
params.tcga_counts_link = "http://duffel.rail.bio/recount/v2/TCGA/counts_gene.tsv.gz"
params.tcga_metadata_link = "http://duffel.rail.bio/recount/TCGA/TCGA.tsv"
params.gencode_link = "ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_25/gencode.v25.annotation.gtf.gz"
ch_gtex_counts_link = Channel.value(params.gtex_counts_link)
ch_gtex_metadata_link = Channel.value(params.gtex_metadata_link)
ch_tcga_counts_link = Channel.value(params.tcga_counts_link)
ch_tcga_metadata_link = Channel.value(params.tcga_metadata_link)
ch_gtf_file = Channel.value(params.gencode_link)
ch_pathways = Channel.fromPath(params.pathways)
process filter_gtex {
label 'with_cpus'
input:
val gtex_metadata_file from ch_gtex_metadata_link
val gtex_counts_file from ch_gtex_counts_link
output:
file 'filtered_gtex_counts.tsv' into ch_filtered_gtex_counts
script:
"""
wget $gtex_counts_file
wget $gtex_metadata_file
filter_gtex_counts.py -c counts_gene.tsv.gz -m SRP012682.tsv
"""
}
process filter_tcga {
label 'with_cpus'
input:
val tcga_metadata_file from ch_tcga_metadata_link
val tcga_counts_file from ch_tcga_counts_link
output:
file 'filtered_tcga_counts.tsv' into ch_filtered_tcga_counts
script:
"""
wget $tcga_counts_file
wget $tcga_metadata_file
filter_tcga_counts.py -c counts_gene.tsv.gz -m TCGA.tsv
"""
}
process sort_counts {
label 'with_cpus'
input:
file filtered_tcga_counts from ch_filtered_tcga_counts
file filtered_gtex_counts from ch_filtered_gtex_counts
output:
file 'healthy_counts.tsv' into ch_healthy_counts
file 'cancer_counts.tsv' into ch_cancer_counts
script:
"""
sort_counts_types.py -g $filtered_gtex_counts -t $filtered_tcga_counts
"""
}
process get_gene_lengths {
label 'with_cpus'
input:
val gtf from ch_gtf_file
output:
file 'gencode.v25.annotation.gtf.genelength' into ch_genelengths
script:
"""
wget $gtf
gunzip gencode.v25.annotation.gtf.gz
gtftools.py -l gencode.v25.annotation.gtf.genelength -c 1-22,X,Y,MT gencode.v25.annotation.gtf
"""
}
process tpm_conversion {
label 'with_cpus'
publishDir "${params.outdir}/tpm_conversion", mode: 'copy'
cpus = 8
memory '16 GB'
input:
file healthy_counts from ch_healthy_counts
file cancer_counts from ch_cancer_counts
file genelengths from ch_genelengths
output:
file 'healthy_tpm.tsv' into ch_healthy_tpm
file 'cancer_tpm.tsv' into ch_cancer_tpm
script:
"""
compute_tpm.py -i $cancer_counts -o cancer_tpm.tsv -p 8 -g $genelengths
compute_tpm.py -i $healthy_counts -o healthy_tpm.tsv -p 8 -g $genelengths
"""
}
process reduce_to_kegg_pathways {
label 'with_cpus'
publishDir "${params.outdir}/intermediate_results", mode: 'copy'
input:
file liver_normal_tpm from ch_healthy_tpm
file liver_cancer_tpm from ch_cancer_tpm
file pathways from ch_pathways
output:
file 'tpm_liver_cancerpathways_normal.tsv' into ch_normal_pathways_tpm
file 'tpm_liver_cancerpathways_cancer.tsv' into ch_cancer_pathways_tpm
script:
"""
reduce_to_kegg_pathways.py -n $liver_normal_tpm -c $liver_cancer_tpm -t liver_cancerpathways -hp $pathways -o .
"""
}
process generate_training_test_datasets {
label 'with_cpus'
publishDir "${params.outdir}/intermediate_results", mode: 'copy'
input:
file normal_pathways_tpm from ch_normal_pathways_tpm
file cancer_pathways_tpm from ch_cancer_pathways_tpm
output:
file 'train.tsv' into ch_training_data
file 'test.tsv' into ch_test_data
script:
"""
generate_train_test_subset.py -n $normal_pathways_tpm -c $cancer_pathways_tpm
"""
}
process predict_lcep {
echo true
label 'with_all_gpus'
publishDir "${params.outdir}/results", mode: 'copy'
input:
file to_predict from ch_test_data
output:
file 'predictions.csv' into ch_predicted
script:
"""
lcep-package --input $to_predict --output predictions.csv --cuda
"""
}
process run_system_intelligence {
publishDir "${params.outdir}/results", mode: 'copy'
label 'with_all_gpus'
output:
file 'system_intelligence.html'
file 'system_intelligence.json'
script:
"""
system-intelligence all --output_format json --generate_html_table --output system_intelligence.json
"""
}