granie bug fixed

src/methods/multi_omics/granie_ns/main.nf

@@ -8,7 +8,7 @@ workflow run_wf {
     | granie.run(
       fromState: [
               multiomics_rna_r: "multiomics_rna_r",
-              multiomics_ata_r: "multiomics_ata_r",
+              multiomics_atac_r: "multiomics_atac_r",
               num_workers: "num_workers"
               ],
       toState: [prediction:"prediction"]

src/robustness_analysis/add_noise_grn.py

@@ -5,7 +5,7 @@
 layer = 'scgen_pearson'
 grn_folder = 'resources/grn_models'
 grn_folder_noised = 'resources/supplementary/grn_models_noised'
-noise_ratio = 0.2
+noise_ratio = 0.5
 # permute_ratio = 0.2
 
 # Ensure the output folder exists

src/workflows/robustness_analysis/config.vsh.yaml

@@ -0,0 +1,28 @@
+
+functionality:
+  name: run_robustness_analysis
+  namespace: "workflows"
+  info:
+    label: run_robustness_analysis
+    summary: "Evaluates GRNs and provides scores using regression analysis."
+
+
+  resources:
+    - type: nextflow_script
+      path: main.nf
+      entrypoint: run_wf
+    - type: file
+      path: ../../api/task_info.yaml
+  dependencies:
+    - name: common/extract_metadata
+      repository: openproblemsv2
+    - name: metrics/regression_1
+  repositories:
+    - name: openproblemsv2
+      type: github
+      repo: openproblems-bio/openproblems-v2
+      tag: main_build
+platforms:
+  - type: nextflow
+    directives:
+      label: [ midtime, midmem, lowcpu ]

src/workflows/robustness_analysis/main.nf

@@ -0,0 +1,129 @@
+
+workflow auto {
+  findStatesTemp(params, meta.config)
+    | meta.workflow.run(
+      auto: [publish: "state"]
+    )
+}
+
+workflow run_wf {
+  take:
+  input_ch
+
+  main:
+
+  // construct list of metrics
+  metrics = [
+    regression_1
+  ]
+
+  /***************************
+   * RUN METRICS *
+   ***************************/
+  score_ch = input_ch
+    | map{ id, state ->
+        [id, state + ["_meta": [join_id: id]]]
+      }
+
+    | positive_control.run(
+      runIf: { id, state ->
+        state.method_id == 'positive_control'
+      },
+      fromState: [
+        perturbation_data: "perturbation_data",
+        layer: "layer",
+        tf_all: "tf_all"
+      ],
+      toState: {id, output, state ->
+        state + [
+          prediction: output.prediction
+        ]
+      }
+    )
+    | negative_control.run(
+      runIf: { id, state ->
+        state.method_id == 'negative_control'
+      },
+      fromState: [
+        perturbation_data: "perturbation_data"
+      ],
+      toState: {id, output, state ->
+        state + [
+          prediction: output.prediction
+        ]
+      }
+    )
+
+    // run all metrics
+    | runEach(
+      components: metrics,
+      id: { id, state, comp ->
+        id + "." + comp.config.functionality.name
+      },
+      // use 'fromState' to fetch the arguments the component requires from the overall state
+      fromState: [
+        perturbation_data: "perturbation_data",
+        layer: "layer", 
+        prediction: "prediction",
+        subsample: "subsample",
+        reg_type: "reg_type",
+        method_id: "method_id",
+        max_workers: "max_workers",
+        consensus: "consensus"
+      ],
+      // use 'toState' to publish that component's outputs to the overall state
+      toState: { id, output, state, comp ->
+        state + [
+          metric_id: comp.config.functionality.name,
+          metric_output: output.score
+        ]
+      }
+    )
+
+  output_ch = score_ch
+
+    // extract the scores
+    | extract_metadata.run(
+      key: "extract_scores",
+      fromState: [input: "metric_output"],
+      toState: { id, output, state ->
+        state + [
+          score_uns: readYaml(output.output).uns
+        ]
+      }
+    )
+
+    | joinStates { ids, states ->
+      assert states[0]._meta, "no _meta found in state[0]"
+      // store the metric configs in a file
+      def metric_configs = metrics.collect{it.config}
+      def metric_configs_yaml_blob = toYamlBlob(metric_configs)
+      def metric_configs_file = tempFile("metric_configs.yaml")
+      metric_configs_file.write(metric_configs_yaml_blob)
+
+      def task_info_file = meta.resources_dir.resolve("task_info.yaml")
+
+      // store the scores in a file
+      def score_uns = states.collect{it.score_uns}
+      def score_uns_yaml_blob = toYamlBlob(score_uns)
+      def score_uns_file = tempFile("score_uns.yaml")
+      score_uns_file.write(score_uns_yaml_blob)
+
+      def new_state = [
+        metric_configs: metric_configs_file,
+        scores: score_uns_file,
+        _meta: states[0]._meta
+      ]
+
+      ["output", new_state]
+    }
+
+    // merge all of the output data 
+    | joinStates{ ids, states ->
+      def mergedStates = states.inject([:]) { acc, m -> acc + m }
+      [ids[0], mergedStates]
+    }
+
+  emit:
+  output_ch
+}