Files
digital-trial/test_no_bt.nf
Olamide Isreal 9e75f44f1a Digital Trials pipeline configured for WES
Source-only snapshot of the cluster branch for WES execution. Large
reference files (HPA/MANE/ensemble FASTA, model weights, ~597 MB) are
omitted: they are baked into the container images at build time and
mounted from the dreamdock-data PVC at runtime, and exceed the Gitea
request size limit.

Pipeline entry point is main.nf, which orchestrates the biotransformer,
conplex and tissue modules as a single workflow. Ligand inputs are read
from the eureka workspace; protein_zarr and chembl_db come from the
dreamdock-data PVC.
2026-07-27 21:59:52 +01:00

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nextflow.enable.dsl=2
// Digital-trials pipeline WITHOUT biotransformer.
// Metabolites are supplied externally (e.g. the consolidated final-metabolites
// dir from prior gabe runs). Otherwise identical to test.nf.
//
// New required param vs test.nf:
// params.metabolites - dir of `<stem>_out.txt` files matching ligand `<stem>.csv`
// Dropped (no biotransformer/chembl):
// container_biotransformer, container_chembl, bt_* knobs, chembl_db, mode
params.container_conplex = 'harbor.cluster.omic.ai/omic/digitaltrials/conplex_dig_pat@sha256:7a3523dba6fa01e3adc9cb79af5e1dcbd2a19d9f92e37cd10df462766078ede3'
params.container_tissue = 'harbor.cluster.omic.ai/omic/digitaltrials/tissue:1.0.6'
params.container_preprocess = 'harbor.cluster.omic.ai/omic/metabolite-screen@sha256:872c395e21abd4afea4185b269a8218da4737bd7adbb2cbe2bdf9a1b9c70db17'
params.container_mass_screen = 'harbor.cluster.omic.ai/omic/metabolite-screen:adaptive-1.1.1'
params.containerOptions = '--rm'
params.project_name = 'test_no_bt'
//CONPLEX
params.keep_enst = 'false'
params.conplex_initial_memory = 5
params.conplex_growth_memory = 15
params.conplex_max_retries = 1
params.conplex_fail_action = 'ignore'
params.threshold = 0.65
params.protein_network_threshold = 0.65
// NETWORK_ENRICHMENT (string-db)
params.string_max_forks = 5
params.string_max_retries = 1
params.string_fail_action = 'ignore'
params.string_initial_memory = 1
params.string_growth_memory = 2
// TISSUE_DISTRIBUTION + BIO_METRICS
params.tissue_initial_memory = 5
params.tissue_growth_memory = 5
params.tissue_max_retries = 2
params.tissue_fail_action = 'ignore'
params.bio_initial_memory = 5
params.bio_growth_memory = 5
params.bio_max_retries = 2
params.bio_fail_action = 'ignore'
// ========================================= FILEPATHS ===================================================
params.outdir = '/mnt/omic-next-apis/wes/digital_trials/'
params.ligands = '/mnt/dreamdock-data/digital_trials/input/test_multitaget'
params.metabolites = '/mnt/dreamdock-data/digital_trials/input/test_metabolites'
params.mutated_protein_fasta = '/mnt/dreamdock-data/digital_trials/input/blank'
params.protein_zarr = '/mnt/dreamdock-data/digital_trials/zarr/protein_seq.zarr'
// =====================================================================================================================================
include { CONPLEX as CONPLEX_ALL } from './main_conplex.nf'
include { PREPROCESS_PROTEIN } from './main_conplex.nf'
include { NETWORK_ENRICHMENT } from './main_conplex.nf'
include { TISSUE_DISTRIBUTION } from './main_tissue.nf'
include { BIO_METRICS } from './main_tissue.nf'
workflow {
lig_ch = Channel.fromPath("${params.ligands}/*.csv")
metabolite_ch = Channel.fromPath("${params.metabolites}/*_out.txt")
protein_fasta = Channel
.fromPath("${params.mutated_protein_fasta}/*.fasta")
.collect()
protein_zarr = PREPROCESS_PROTEIN(protein_fasta).collect().map { it[0] }
pre_protein_zarr = Channel.fromPath(params.protein_zarr)
merged_zarr = protein_zarr.concat(pre_protein_zarr).collect()
lig_with_id = lig_ch.map { csv ->
[csv.simpleName, csv]
}
metabolite_with_id = metabolite_ch.map { txt ->
def name = txt.simpleName.replaceAll(/_out$/, '')
[name, txt]
}
matched_ch = lig_with_id.join(metabolite_with_id)
CONPLEX_ALL(matched_ch, merged_zarr)
conplex_interactions_ch = CONPLEX_ALL.out.map { id, drug, interactions -> interactions }
NETWORK_ENRICHMENT(conplex_interactions_ch)
TISSUE_DISTRIBUTION(conplex_interactions_ch)
biometric_ch = matched_ch.join(CONPLEX_ALL.out)
BIO_METRICS(biometric_ch)
}