Add: merge_pvalues and create_consensus modules

micone/pipelines/configs/network_inference.config

@@ -59,6 +59,13 @@ params {
                 // FIXME: This should ideally be passed through the sample_sheet
                 metadata_file = ""
             }
+            'merge_pvalues' {}
+            'create_consensus' {
+                method = 'scaled_sum'
+                parameter = 0.3
+                pvalue_filter = "true"
+                interaction_filter = "true"
+            }
         }
     }
 }

micone/pipelines/modules/network_inference/network/create_consensus.nf

@@ -0,0 +1,22 @@
+include { getHierarchy } from '../../../functions/functions.nf'
+
+process create_consensus {
+    label 'micone'
+    tag "${meta.id}"
+    publishDir "${params.output_dir}/${f[0]}/network/${f[1]}/${directory}/${meta.id}",
+        mode: 'copy',
+        overwrite: true
+    input:
+        tuple val(meta), file('*_network.json')
+    output:
+        tuple val(meta), file('*_network.json')
+    script:
+        String task_process = "${task.process}"
+        f = getHierarchy(task_process)
+        directory = "${meta.denoise_cluster}-${meta.chimera_checking}-${meta.tax_assignment}-${meta.tax_level}-${meta.network_inference}"
+        method = params.network_inference.network['create_consensus']['method']
+        parameter = params.network_inference.network['create_consensus']['parameter']
+        pvalue_filter = params.network_inference.network['create_consensus']['pvalue_filter']
+        interaction_filter = params.network_inference.network['create_consensus']['interaction_filter']
+        template 'network_inference/network/create_consensus.py'
+}

micone/pipelines/modules/network_inference/network/merge_pvalues.nf

@@ -0,0 +1,18 @@
+include { getHierarchy } from '../../../functions/functions.nf'
+
+process merge_pvalues {
+    label 'micone'
+    tag "${meta.id}"
+    publishDir "${params.output_dir}/${f[0]}/network/${f[1]}/${directory}/${meta.id}",
+        mode: 'copy',
+        overwrite: true
+    input:
+        tuple val(meta), file('*_network.json')
+    output:
+        tuple val(meta), file('*_network.json')
+    script:
+        String task_process = "${task.process}"
+        f = getHierarchy(task_process)
+        directory = "${meta.denoise_cluster}-${meta.chimera_checking}-${meta.tax_assignment}-${meta.tax_level}-${meta.network_inference}"
+        template 'network_inference/network/merge_pvalues.py'
+}

micone/pipelines/modules/network_inference/network_inference_workflow.nf

@@ -15,6 +15,8 @@ include { mldm_workflow } from './direct/mldm_workflow.nf'
 // Network imports
 include { make_network_with_pvalue } from './network/make_network_with_pvalue.nf'
 include { make_network_without_pvalue } from './network/make_network_without_pvalue.nf'
+include { merge_pvalues } from './network/merge_pvalues.nf'
+include { create_consensus } from './network/create_consensus.nf'
 
 // Main workflow
 workflow network_inference_workflow {
@@ -46,13 +48,20 @@ workflow network_inference_workflow {
                             mldm_workflow.out
                         )
 
+    // Correlation method output
     make_network_with_pvalue(corr_output)
+    merge_pvalues(make_network_with_pvalue.out.collect())
+
+    // Direct method output
     make_network_without_pvalue(direct_output)
 
-    network_channel = make_network_with_pvalue.out.mix(make_network_without_pvalue.out)
+    // Create consensus
+    network_channel = merge_pvalues.out.flatten().mix(make_network_without_pvalue.out)
+    create_consensus(network_channel.out.collect())
+
 
     emit:
         // all processes have publishDir
         // tuple val(meta), file("*.json")
-        network_channel
+        create_consensus.out
 }

micone/pipelines/templates/network_inference/network/create_consensus.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+
+import pathlib
+from typing import List
+
+from micone import Network, NetworkGroup
+
+
+def main(
+    base_name: str,
+    network_files: List[pathlib.Path],
+    method: str,
+    parameter: float,
+    pvalue_filter: bool,
+    interaction_filter: bool,
+) -> None:
+    networks: List[Network] = []
+    for network_file in network_files:
+        networks.append(Network.load_json(str(network_file)))
+    network_group = NetworkGroup(networks)
+    cids = [ctx["cid"] for ctx in network_group.contexts]
+    filtered_network_group = network_group.filter(
+        pvalue_filter=pvalue_filter, interaction_filter=interaction_filter
+    )
+    consensus_network_group = filtered_network_group.get_consensus_network(
+        cids, method=method, parameter=parameter
+    )
+    consensus_network_group.write(base_name + "_network.json")
+
+
+if __name__ == "__main__":
+    BASE_NAME = "${meta.id}"
+    METHOD = "${method}"
+    PARAMETER = float("${parameter}")
+    PVALUE_FILTER = True if "${pvalue_filter}" == "true" else False
+    INTERACTION_FILTER = True if "${interaction_filter}" == "true" else False
+    NETWORK_FILES = list(pathlib.Path().glob("*.json"))
+    main(BASE_NAME, NETWORK_FILES, METHOD, PARAMETER, PVALUE_FILTER, INTERACTION_FILTER)

micone/pipelines/templates/network_inference/network/merge_pvalues.py

@@ -0,0 +1,22 @@
+#!/usr/bin/env python3
+
+import pathlib
+from typing import List
+
+from micone import Network, NetworkGroup
+
+
+def main(base_name: str, network_files: List[pathlib.Path]) -> None:
+    networks: List[Network] = []
+    for network_file in network_files:
+        networks.append(Network.load_json(str(network_file)))
+    network_group = NetworkGroup(networks)
+    cids = [ctx["cid"] for ctx in network_group.contexts]
+    merged_network_group = network_group.combine_pvalues(cids)
+    merged_network_group.write(base_name + "_network.json", split_files=True)
+
+
+if __name__ == "__main__":
+    BASE_NAME = "${meta.id}"
+    NETWORK_FILES = list(pathlib.Path().glob("*.json"))
+    main(BASE_NAME, NETWORK_FILES)