From 20747c8d0b90553f261fdda22e194b85c3f0f767 Mon Sep 17 00:00:00 2001
From: James Kent <jamesdkent21@gmail.com>
Date: Fri, 22 Dec 2023 10:54:56 -0600
Subject: [PATCH 1/3] change names and modify files

---
 .dockerignore                                 |      2 +-
 compose_runner/__init__.py                    |      0
 .../__pycache__/__init__.cpython-38.pyc       |    Bin 0 -> 141 bytes
 compose_runner/__pycache__/run.cpython-38.pyc |    Bin 0 -> 9889 bytes
 compose_runner/cli.py                         |     25 +
 compose_runner/run.py                         |    421 +
 .../tests/__pycache__/__init__.cpython-38.pyc |    Bin 0 -> 147 bytes
 .../test_run.cpython-38-pytest-7.4.3.pyc      |    Bin 0 -> 2339 bytes
 .../test_run/test_download_bundle.yaml        |    964 +
 .../test_run/test_run_database_workflow.yaml  | 104965 +++++++++++++++
 .../test_run_group_comparison_workflow.yaml   |  48633 +++++++
 ..._run_string_group_comparison_workflow.yaml |  41538 ++++++
 .../cassettes/test_run/test_run_workflow.yaml |  46547 +++++++
 compose_runner/tests/test_run.py              |     56 +
 pyproject.toml                                |      7 +-
 15 files changed, 243153 insertions(+), 5 deletions(-)
 create mode 100644 compose_runner/__init__.py
 create mode 100644 compose_runner/__pycache__/__init__.cpython-38.pyc
 create mode 100644 compose_runner/__pycache__/run.cpython-38.pyc
 create mode 100644 compose_runner/cli.py
 create mode 100644 compose_runner/run.py
 create mode 100644 compose_runner/tests/__pycache__/__init__.cpython-38.pyc
 create mode 100644 compose_runner/tests/__pycache__/test_run.cpython-38-pytest-7.4.3.pyc
 create mode 100644 compose_runner/tests/cassettes/test_run/test_download_bundle.yaml
 create mode 100644 compose_runner/tests/cassettes/test_run/test_run_database_workflow.yaml
 create mode 100644 compose_runner/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
 create mode 100644 compose_runner/tests/cassettes/test_run/test_run_string_group_comparison_workflow.yaml
 create mode 100644 compose_runner/tests/cassettes/test_run/test_run_workflow.yaml
 create mode 100644 compose_runner/tests/test_run.py

diff --git a/.dockerignore b/.dockerignore
index f39c08f..5529ddf 100644
--- a/.dockerignore
+++ b/.dockerignore
@@ -1,4 +1,4 @@
 .runner
 .nsc
 .pytest_cache
-pynsc/tests/cassettes
+compose_runner/tests/cassettes
diff --git a/compose_runner/__init__.py b/compose_runner/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/compose_runner/__pycache__/__init__.cpython-38.pyc b/compose_runner/__pycache__/__init__.cpython-38.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..4290fd94d543de0eba1b13e05f95dae1491b0399
GIT binary patch
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diff --git a/compose_runner/__pycache__/run.cpython-38.pyc b/compose_runner/__pycache__/run.cpython-38.pyc
new file mode 100644
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diff --git a/compose_runner/cli.py b/compose_runner/cli.py
new file mode 100644
index 0000000..e23e331
--- /dev/null
+++ b/compose_runner/cli.py
@@ -0,0 +1,25 @@
+import click
+
+from compose_runner.run import run
+
+
+@click.command()
+@click.argument("meta-analysis-id", required=True)
+@click.option("--result-dir", help="The directory to save results to.")
+@click.option(
+    "environment",
+    "--environment",
+    type=click.Choice(["production", "staging", "local"], case_sensitive=False),
+    default="production",
+    help="DEVELOPER USE ONLY Use another server instead of production server.",
+)
+@click.option("nsc_key", "--nsc-key", help="Neurosynth Compose api key.")
+@click.option("nv_key", "--nv-key", help="Neurovault api key.")
+@click.option("--no-upload", is_flag=True, help="Do not upload results.")
+def cli(meta_analysis_id, environment, result_dir, nsc_key, nv_key, no_upload):
+    """Execute and upload a meta-analysis workflow.
+
+    META_ANALYSIS_ID is the id of the meta-analysis on neurosynth-compose.
+    """
+    url, _ = run(meta_analysis_id, environment, result_dir, nsc_key, nv_key, no_upload)
+    print(url)
diff --git a/compose_runner/run.py b/compose_runner/run.py
new file mode 100644
index 0000000..341f428
--- /dev/null
+++ b/compose_runner/run.py
@@ -0,0 +1,421 @@
+from importlib import import_module
+from pathlib import Path
+import gzip
+import json
+import io
+
+import requests
+
+# import neurosynth_compose_sdk
+# from neurosynth_compose_sdk.api.compose_api import ComposeApi
+# import neurostore_sdk
+# from neurostore_sdk.api.store_api import StoreApi
+from nimare.workflows import CBMAWorkflow, PairwiseCBMAWorkflow
+from nimare.meta.cbma.base import CBMAEstimator, PairwiseCBMAEstimator
+from nimare.nimads import Studyset, Annotation
+from nimare.meta.cbma import ALE, ALESubtraction, SCALE
+
+
+def gen_database_url(branch, database):
+    return f"https://github.com/neurostuff/neurostore_database/raw/{branch}/{database}.json.gz"
+
+
+class Runner:
+    """Runner for executing and uploading a meta-analysis workflow."""
+
+    def __init__(
+        self,
+        meta_analysis_id,
+        environment="production",
+        result_dir=None,
+        nsc_key=None,
+        nv_key=None,
+    ):
+        # the meta-analysis id associated with this run
+        self.meta_analysis_id = meta_analysis_id
+
+        if environment == "staging":
+            # staging
+            self.compose_url = "https://synth.neurostore.xyz/api"
+            self.store_url = "https://neurostore.xyz/api"
+            self.reference_studysets = {
+                "neurosynth": gen_database_url("staging", "neurosynth"),
+                "neuroquery": gen_database_url("staging", "neuroquery"),
+                "neurostore": gen_database_url("staging", "neurostore"),
+                "neurostore_small": gen_database_url("staging", "neurostore_small"),
+            }
+        elif environment == "local":
+            self.compose_url = "http://localhost:81/api"
+            self.store_url = "http://localhost:80/api"
+            self.reference_studysets = {
+                "neurosynth": gen_database_url("staging", "neurosynth"),
+                "neuroquery": gen_database_url("staging", "neuroquery"),
+                "neurostore": gen_database_url("staging", "neurostore"),
+                "neurostore_small": gen_database_url("staging", "neurostore_small"),
+            }
+        else:
+            # production
+            self.compose_url = "https://compose.neurosynth.org/api"
+            self.store_url = "https://neurostore.org/api"
+            self.reference_studysets = {
+                "neurosynth": gen_database_url("main", "neurosynth"),
+                "neuroquery": gen_database_url("main", "neuroquery"),
+                "neurostore": gen_database_url("main", "neurostore"),
+            }
+
+        # Enter a context with an instance of the API client
+        # compose_configuration = neurosynth_compose_sdk.Configuration(
+        #     host=self.compose_url
+        # )
+        # store_configuration = neurostore_sdk.Configuration(host=self.store_url)
+        # compose_client = neurosynth_compose_sdk.ApiClient(compose_configuration)
+        # store_client = neurostore_sdk.ApiClient(store_configuration)
+        # self.compose_api = ComposeApi(compose_client)
+        # self.store_api = StoreApi(store_client)
+
+        # initialize inputs
+        self.cached_studyset = None
+        self.cached_annotation = None
+        self.cached_specification = None
+        self.first_dataset = None
+        self.second_dataset = None
+        self.estimator = None
+        self.corrector = None
+
+        # initialize api-keys
+        self.nsc_key = nsc_key  # neurosynth compose key to upload to neurosynth compose
+        self.nv_key = nv_key  # neurovault key to upload to neurovault
+
+        # result directory
+        if result_dir is None:
+            self.result_dir = Path.cwd() / "results"
+        else:
+            self.result_dir = Path(result_dir)
+
+        # whether the inputs were cached from neurostore
+        self.cached = True
+
+        # initialize outputs
+        self.result_id = None
+        self.meta_results = None  # the meta-analysis result output from nimare
+        self.results_object = (
+            None  # the result object represented on neurosynth compose
+        )
+
+    def run_workflow(self, no_upload=False):
+        self.download_bundle()
+        self.process_bundle()
+        self.run_meta_analysis()
+        if not no_upload:
+            self.create_result_object()
+            self.upload_results()
+
+    def download_bundle(self):
+        meta_analysis = requests.get(
+            f"{self.compose_url}/meta-analyses/{self.meta_analysis_id}?nested=true"
+        ).json()
+        # meta_analysis = self.compose_api.meta_analyses_id_get(
+        #     id=self.meta_analysis_id, nested=True
+        # ).to_dict()  # does not currently return run_key
+
+        # check to see if studyset and annotation are cached
+        studyset_dict = annotation_dict = None
+        if meta_analysis["studyset"]:
+            studyset_dict = meta_analysis["studyset"]["snapshot"]
+            self.cached_studyset = (
+                None if studyset_dict is None else studyset_dict.get("snapshot", None)
+            )
+        if meta_analysis["annotation"]:
+            annotation_dict = meta_analysis["annotation"]["snapshot"]
+            self.cached_annotation = (
+                None
+                if annotation_dict is None
+                else annotation_dict.get("snapshot", None)
+            )
+        # if either are not cached, download them from neurostore
+        if self.cached_studyset is None or self.cached_annotation is None:
+            self.cached_studyset = requests.get(
+                (
+                    f"{self.store_url}/studysets/"
+                    f"{meta_analysis['studyset']['neurostore_id']}?nested=true"
+                )
+            ).json()
+            self.cached_annotation = requests.get(
+                f"{self.store_url}/annotations/{meta_analysis['annotation']['neurostore_id']}"
+            ).json()
+            # set cached to false
+            self.cached = False
+        # retrieve specification
+        self.cached_specification = meta_analysis["specification"]
+
+        # run key for running this particular meta-analysis
+        self.nsc_key = meta_analysis["run_key"]
+
+    def apply_filter(self, studyset, annotation):
+        """
+        Apply filter to studyset.
+            Options:
+                - bool: filter by boolean column
+                  can be single or multiple conditions
+                - string: filter by string column
+                  can be single or multiple conditions
+                - database_studyset: use a reference studyset
+                  only useful for multiple conditions
+        """
+        column = self.cached_specification["filter"]
+        column_type = self.cached_annotation["note_keys"][f"{column}"]
+        conditions = self.cached_specification.get("conditions", [])
+        database_studyset = self.cached_specification.get("database_studyset")
+        weights = self.cached_specification.get("weights", [])
+        weight_conditions = {w: c for c, w in zip(conditions, weights)}
+
+        if not (conditions or weights) and column_type != "boolean":
+            raise ValueError(
+                f"Column type {column_type} requires a conditions and weights."
+            )
+
+        # get analysis ids for the first studyset
+        if column_type == "boolean":
+            analysis_ids = [
+                n.analysis.id for n in annotation.notes if n.note[f"{column}"]
+            ]
+
+        elif column_type == "string":
+            analysis_ids = [
+                n.analysis.id
+                for n in annotation.notes
+                if n.note[f"{column}"] == weight_conditions[1]
+            ]
+        else:
+            raise ValueError(f"Column type {column_type} not supported.")
+
+        first_studyset = studyset.slice(analyses=analysis_ids)
+        first_studyset = first_studyset.combine_analyses()
+
+        # if there is only one condition, return the first studyset
+        if len(conditions) <= 1 and not database_studyset:
+            return first_studyset, None
+
+        elif len(conditions) == 2 and database_studyset:
+            raise ValueError("Cannot have multiple conditions and a database studyset.")
+
+        elif len(conditions) == 2 and not database_studyset:
+            second_analysis_ids = [
+                n.analysis.id
+                for n in annotation.notes
+                if n.note[f"{column}"] == weight_conditions[-1]
+            ]
+            second_studyset = studyset.slice(analyses=second_analysis_ids)
+            second_studyset = second_studyset.combine_analyses()
+
+            return first_studyset, second_studyset
+
+        elif len(conditions) <= 1 and database_studyset:
+            # Download the gzip file
+            response = requests.get(self.reference_studysets[database_studyset])
+
+            # Check if the request was successful
+            if response.status_code != 200:
+                raise ValueError(
+                    f"Could not download reference studyset {database_studyset}."
+                )
+            # Wrap the content of the response in a BytesIO object
+            gzip_content = io.BytesIO(response.content)
+
+            # Decompress the gzip content
+            with gzip.GzipFile(fileobj=gzip_content, mode="rb") as gz_file:
+                # Read and decode the JSON data
+                json_data = gz_file.read().decode("utf-8")
+
+                # Load the JSON data into a dictionary
+                reference_studyset_dict = json.loads(json_data)
+
+            reference_studyset = Studyset(reference_studyset_dict)
+
+            # get study ids from studyset
+            study_ids = set([s.id for s in studyset.studies])
+
+            # reference study ids
+            reference_study_ids = set([s.id for s in reference_studyset.studies])
+
+            keep_study_ids = reference_study_ids - study_ids
+
+            # get analysis ids from reference studyset
+            analysis_ids = [
+                a.id
+                for s in reference_studyset.studies
+                for a in s.analyses
+                if s.id in keep_study_ids
+            ]
+            second_studyset = reference_studyset.slice(analyses=analysis_ids)
+            second_studyset = second_studyset.combine_analyses()
+
+            return first_studyset, second_studyset
+
+    def process_bundle(self):
+        studyset = Studyset(self.cached_studyset)
+        annotation = Annotation(self.cached_annotation, studyset)
+        first_studyset, second_studyset = self.apply_filter(studyset, annotation)
+        first_dataset = first_studyset.to_dataset()
+        second_dataset = (
+            second_studyset.to_dataset() if second_studyset is not None else None
+        )
+        estimator, corrector = self.load_specification()
+        estimator, corrector = self.validate_specification(
+            estimator, corrector, first_dataset, second_dataset
+        )
+        self.first_dataset = first_dataset
+        self.second_dataset = second_dataset
+        self.estimator = estimator
+        self.corrector = corrector
+
+    def create_result_object(self):
+        # take a snapshot of the studyset and annotation (before running the workflow)
+        headers = {"Compose-Upload-Key": self.nsc_key}
+        data = {"meta_analysis_id": self.meta_analysis_id}
+        if not self.cached:
+            data.update(
+                {
+                    "studyset_snapshot": self.cached_studyset,
+                    "annotation_snapshot": self.cached_annotation,
+                }
+            )
+        resp = requests.post(
+            f"{self.compose_url}/meta-analysis-results",
+            json=data,
+            headers=headers,
+        )
+        self.result_id = resp.json().get("id", None)
+        if self.result_id is None:
+            raise ValueError(f"Could not create result for {self.meta_analysis_id}")
+
+    def run_meta_analysis(self):
+        if self.second_dataset and isinstance(self.estimator, PairwiseCBMAEstimator):
+            workflow = PairwiseCBMAWorkflow(
+                estimator=self.estimator,
+                corrector=self.corrector,
+                diagnostics="focuscounter",
+                output_dir=self.result_dir,
+            )
+            self.meta_results = workflow.fit(self.first_dataset, self.second_dataset)
+        elif self.second_dataset is None and isinstance(self.estimator, CBMAEstimator):
+            workflow = CBMAWorkflow(
+                estimator=self.estimator,
+                corrector=self.corrector,
+                diagnostics="focuscounter",
+                output_dir=self.result_dir,
+            )
+            self.meta_results = workflow.fit(self.first_dataset, self.second_dataset)
+        else:
+            raise ValueError(
+                f"Estimator {self.estimator} and datasets {self.first_dataset} and {self.second_dataset} are not compatible."
+            )
+
+    def upload_results(self):
+        statistical_maps = [
+            (
+                "statistical_maps",
+                open(self.result_dir / (m + ".nii.gz"), "rb"),
+            )
+            for m in self.meta_results.maps.keys()
+            if not m.startswith("label_")
+        ]
+        cluster_tables = [
+            (
+                "cluster_tables",
+                open(self.result_dir / (f + ".tsv"), "rb"),
+            )
+            for f, df in self.meta_results.tables.items()
+            if "clust" in f and not df.empty
+        ]
+
+        diagnostic_tables = [
+            (
+                "diagnostic_tables",
+                open(self.result_dir / (f + ".tsv"), "rb"),
+            )
+            for f, df in self.meta_results.tables.items()
+            if "clust" not in f and df is not None
+        ]
+        files = statistical_maps + cluster_tables + diagnostic_tables
+
+        headers = {"Compose-Upload-Key": self.nsc_key}
+        self.results_object = requests.put(
+            f"{self.compose_url}/meta-analysis-results/{self.result_id}",
+            files=files,
+            json={"method_description": self.meta_results.description_},
+            headers=headers,
+        )
+
+    def load_specification(self):
+        """Returns function to run analysis on dataset."""
+        spec = self.cached_specification
+        est_mod = import_module(".".join(["nimare", "meta", spec["type"].lower()]))
+        estimator = getattr(est_mod, spec["estimator"]["type"])
+        if spec["estimator"].get("args"):
+            est_args = {**spec["estimator"]["args"]}
+            if est_args.get("**kwargs") is not None:
+                for k, v in est_args["**kwargs"].items():
+                    est_args[k] = v
+                del est_args["**kwargs"]
+            estimator_init = estimator(**est_args)
+        else:
+            estimator_init = estimator()
+
+        if spec.get("corrector"):
+            cor_mod = import_module(".".join(["nimare", "correct"]))
+            corrector = getattr(cor_mod, spec["corrector"]["type"])
+            if spec["corrector"].get("args"):
+                cor_args = {**spec["corrector"]["args"]}
+                if cor_args.get("**kwargs") is not None:
+                    for k, v in cor_args["**kwargs"].items():
+                        cor_args[k] = v
+                    del cor_args["**kwargs"]
+                corrector_init = corrector(**cor_args)
+            else:
+                corrector_init = corrector()
+        else:
+            corrector_init = None
+
+        return estimator_init, corrector_init
+
+    def validate_specification(
+        self, estimator, corrector, dataset, second_dataset=None
+    ):
+        if (
+            isinstance(estimator, (ALE, ALESubtraction, SCALE))
+            and estimator.kernel_transformer.sample_size is not None
+        ):
+            if any(dataset.metadata["sample_sizes"].isnull()):
+                raise ValueError(
+                    "Sample size is required for ALE with sample size weighting."
+                )
+        return estimator, corrector
+
+
+def run(
+    meta_analysis_id,
+    environment="production",
+    result_dir=None,
+    nsc_key=None,
+    nv_key=None,
+    no_upload=False,
+):
+    runner = Runner(
+        meta_analysis_id=meta_analysis_id,
+        environment=environment,
+        result_dir=result_dir,
+        nsc_key=nsc_key,
+        nv_key=nv_key,
+    )
+
+    runner.run_workflow(no_upload=no_upload)
+
+    if no_upload:
+        return None, runner.meta_results
+
+    url = "/".join(
+        [runner.compose_url.rstrip("/api"), "meta-analyses", meta_analysis_id]
+    )
+
+    return url, runner.meta_results
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diff --git a/compose_runner/tests/cassettes/test_run/test_download_bundle.yaml b/compose_runner/tests/cassettes/test_run/test_download_bundle.yaml
new file mode 100644
index 0000000..0e0078d
--- /dev/null
+++ b/compose_runner/tests/cassettes/test_run/test_download_bundle.yaml
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+interactions:
+- request:
+    body: null
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      User-Agent:
+      - python-requests/2.28.2
+    method: GET
+    uri: https://synth.neurostore.xyz/api/meta-analyses/3opENJpHxRsH?nested=true
+  response:
+    body:
+      string: !!binary |
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diff --git a/compose_runner/tests/cassettes/test_run/test_run_database_workflow.yaml b/compose_runner/tests/cassettes/test_run/test_run_database_workflow.yaml
new file mode 100644
index 0000000..de28ee5
--- /dev/null
+++ b/compose_runner/tests/cassettes/test_run/test_run_database_workflow.yaml
@@ -0,0 +1,104965 @@
+interactions:
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+    body: null
+    headers:
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+      Accept-Encoding:
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+      Connection:
+      - keep-alive
+      User-Agent:
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diff --git a/compose_runner/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml b/compose_runner/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
new file mode 100644
index 0000000..9708bb8
--- /dev/null
+++ b/compose_runner/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
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diff --git a/compose_runner/tests/cassettes/test_run/test_run_string_group_comparison_workflow.yaml b/compose_runner/tests/cassettes/test_run/test_run_string_group_comparison_workflow.yaml
new file mode 100644
index 0000000..56aca1a
--- /dev/null
+++ b/compose_runner/tests/cassettes/test_run/test_run_string_group_comparison_workflow.yaml
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+      "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [-50.0, -44.0, 8.0], "id": "iZvFohzeF6zA", "image": null, "kind": "unknown",
+      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [60.0, -8.0,
+      -4.0], "id": "v4P6WeYrXqhh", "image": null, "kind": "unknown", "label_id": null,
+      "space": "MNI", "values": []}], "user": null, "weights": []}, {"conditions":
+      [], "description": null, "id": "8KL5SpPjm2eu", "images": [], "name": "19176",
+      "points": [{"coordinates": [-10.0, -28.0, 44.0], "id": "53gJHvYg2ZAT", "image":
+      null, "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [42.0, 16.0, -10.0], "id": "5wRVFvQywHGh", "image": null, "kind": "unknown",
+      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [-46.0, -34.0,
+      42.0], "id": "6PCNqZFVGpmR", "image": null, "kind": "unknown", "label_id": null,
+      "space": "MNI", "values": []}, {"coordinates": [-30.0, 26.0, 4.0], "id": "6ujv2LZeMX2y",
+      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
+      []}, {"coordinates": [42.0, -38.0, 46.0], "id": "75xNy4vWEyTE", "image": null,
+      "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [4.0, 26.0, 48.0], "id": "7nwacGdZNv8V", "image": null, "kind": "unknown", "label_id":
+      null, "space": "MNI", "values": []}], "user": null, "weights": []}], "authors":
+      "Wittfoth M, Schroder C, Schardt DM, Dengler R, Heinze HJ, Kotz SA", "created_at":
+      "2023-05-19T23:38:25.513965+00:00", "description": null, "doi": "10.1093/cercor/bhp106",
+      "id": "8Kr5LfW7Abga", "metadata": null, "name": "On emotional conflict: interference
+      resolution of happy and angry prosody reveals valence-specific effects.", "pmid":
+      "19505993", "publication": "Cerebral cortex (New York, N.Y. : 1991)", "source":
+      "neurosynth", "source_id": "19505993", "source_updated_at": null, "updated_at":
+      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": 2010}, {"analyses":
+      [{"conditions": [], "description": null, "id": "95c2k6ff2Pfh", "images": [],
+      "name": "37742", "points": [{"coordinates": [7.0, 18.0, 19.0], "id": "3f2DGtrmyiWS",
+      "image": null, "kind": "unknown", "label_id": null, "space": "TAL", "values":
+      []}, {"coordinates": [3.0, 4.0, 6.0], "id": "4YxE46FqgFZX", "image": null, "kind":
+      "unknown", "label_id": null, "space": "TAL", "values": []}, {"coordinates":
+      [7.0, 18.0, 19.0], "id": "4inMEKCFjxrS", "image": null, "kind": "unknown", "label_id":
+      null, "space": "TAL", "values": []}, {"coordinates": [6.0, 7.0, 9.0], "id":
+      "7Kau8V3JAMAG", "image": null, "kind": "unknown", "label_id": null, "space":
+      "TAL", "values": []}], "user": null, "weights": []}], "authors": "Lee TM, Liu
+      HL, Hoosain R, Liao WT, Wu CT, Yuen KS, Chan CC, Fox PT, Gao JH", "created_at":
+      "2023-05-19T23:38:25.513965+00:00", "description": null, "doi": "10.1016/S0304-3940(02)00965-5",
+      "id": "xQhZkTxtHGZH", "metadata": null, "name": "Gender differences in neural
+      correlates of recognition of happy and sad faces in  humans assessed by functional
+      magnetic resonance imaging.", "pmid": "12401549", "publication": "Neuroscience
+      letters", "source": "neurosynth", "source_id": "12401549", "source_updated_at":
+      null, "updated_at": "2023-06-21T22:17:27.973390+00:00", "user": null, "year":
+      2002}, {"analyses": [{"conditions": [], "description": null, "id": "38HqPANwZTG2",
+      "images": [], "name": "42004", "points": [{"coordinates": [4.0, 40.0, 22.0],
+      "id": "5ArfJw6UA2ko", "image": null, "kind": "unknown", "label_id": null, "space":
+      "MNI", "values": []}, {"coordinates": [0.0, 46.0, 46.0], "id": "7LimdjsYPq85",
+      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
+      []}], "user": null, "weights": []}], "authors": "Pulkkinen J, Nikkinen J, Kiviniemi
+      V, Maki P, Miettunen J, Koivukangas J, Mukkala S, Nordstrom T, Barnett JH, Jones
+      PB, Moilanen I, Murray GK, Veijola J", "created_at": "2023-05-19T23:38:25.513965+00:00",
+      "description": null, "doi": "10.1016/j.schres.2015.01.039", "id": "6gD4cLusQaGb",
+      "metadata": null, "name": "Functional mapping of dynamic happy and fearful facial
+      expressions in young adults with familial risk for psychosis - Oulu Brain and
+      Mind Study.", "pmid": "25703807", "publication": "Schizophrenia research", "source":
+      "neurosynth", "source_id": "25703807", "source_updated_at": null, "updated_at":
+      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": 2015}, {"analyses":
+      [{"conditions": [], "description": "SPM{F_[12.0,416.0]} - contrast 4: Group
+      X Drug x Emotion", "id": "75fxWNPbZbjv", "images": [{"add_date": "2018-03-25T22:28:21.071437+00:00",
+      "filename": "spmF_WB_GroupXDrugXEmotion.nii.gz", "id": "5ywy83QVhqKa", "space":
+      "MNI", "url": "http://neurovault.org/media/images/3666/spmF_WB_GroupXDrugXEmotion.nii.gz",
+      "user": null, "value_type": "other"}], "name": "spmF WB GroupXDrugXEmotion",
+      "points": [], "user": null, "weights": []}, {"conditions": [], "description":
+      "SPM{T_[41.0]} - contrast 1: Faces > Shapes", "id": "fPbGgVwV6WY4", "images":
+      [{"add_date": "2018-03-25T22:28:21.579847+00:00", "filename": "spmT_WB_ALLFACES%3ESHAPES.nii.gz",
+      "id": "45wqEfAbeyF3", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_WB_ALLFACES%3ESHAPES.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT WB ALLFACES>SHAPES", "points":
+      [], "user": null, "weights": []}, {"conditions": [], "description": "SPM{T_[416.0]}
+      - contrast 1: G1 > G2", "id": "5Aa9eTyM6Z73", "images": [{"add_date": "2018-03-25T22:28:21.975422+00:00",
+      "filename": "spmT_WB_BDD%3EHC.nii.gz", "id": "7g9BASMF7fJf", "space": "MNI",
+      "url": "http://neurovault.org/media/images/3666/spmT_WB_BDD%3EHC.nii.gz", "user":
+      null, "value_type": "T"}], "name": "spmT WB BDD>HC", "points": [], "user": null,
+      "weights": []}, {"conditions": [], "description": "SPM{T_[416.0]} - contrast
+      3: Group x Drug: BDD greater in Oxyt", "id": "7npj8yWwnet4", "images": [{"add_date":
+      "2018-03-25T22:28:22.600766+00:00", "filename": "spmT_WB_GroupXDrug_BDD%3EHC.nii.gz",
+      "id": "5BapE8TLR6gx", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_WB_GroupXDrug_BDD%3EHC.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT WB GroupXDrug BDD>HC", "points":
+      [], "user": null, "weights": []}, {"conditions": [], "description": "SPM{T_[416.0]}
+      - contrast 2: G2 > G1", "id": "6nTZmgpghK4z", "images": [{"add_date": "2018-03-25T22:28:23.026721+00:00",
+      "filename": "spmT_WB_HC%3EBDD.nii.gz", "id": "3BTjSSJUegTE", "space": "MNI",
+      "url": "http://neurovault.org/media/images/3666/spmT_WB_HC%3EBDD.nii.gz", "user":
+      null, "value_type": "T"}], "name": "spmT WB HC>BDD", "points": [], "user": null,
+      "weights": []}, {"conditions": [], "description": "SPM{T_[416.0]} - contrast
+      5: Main Effect of Drug: Oxy > Plac", "id": "4uN7cxX3QSqL", "images": [{"add_date":
+      "2018-03-25T22:28:23.491835+00:00", "filename": "spmT_WB_MainEffectDrug_OXT%3EPBO.nii.gz",
+      "id": "B74DNs6w5yJE", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_WB_MainEffectDrug_OXT%3EPBO.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT WB MainEffectDrug OXT>PBO",
+      "points": [], "user": null, "weights": []}, {"conditions": [], "description":
+      "SPM{T_[416.0]} - contrast 6: Main Effect of Drug: Plac > Oxyt ", "id": "5ZQbnszRa6sF",
+      "images": [{"add_date": "2018-03-25T22:28:23.936669+00:00", "filename": "spmT_WB_MainEffectDrug_PBO%3EOXT.nii.gz",
+      "id": "4iVYzjXoYZjL", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_WB_MainEffectDrug_PBO%3EOXT.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT WB MainEffectDrug PBO>OXT",
+      "points": [], "user": null, "weights": []}, {"conditions": [], "description":
+      "SPM{T_[32.0]} - contrast 1: BDD > HC", "id": "59gY3ro98L28", "images": [{"add_date":
+      "2018-03-25T22:28:24.344432+00:00", "filename": "spmT_gPPI_ANGRY%3ESHAPES_BDD%3EHC.nii.gz",
+      "id": "wCF8fop8MXME", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_gPPI_ANGRY%3ESHAPES_BDD%3EHC.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT gPPI ANGRY>SHAPES BDD>HC",
+      "points": [], "user": null, "weights": []}, {"conditions": [], "description":
+      "SPM{T_[32.0]} - contrast 2: HC > BDD", "id": "7AKSr54RRuDe", "images": [{"add_date":
+      "2018-03-25T22:28:24.736969+00:00", "filename": "spmT_gPPI_ANGRY%3ESHAPES_HC%3EBDD.nii.gz",
+      "id": "jzsrud3nk5ba", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_gPPI_ANGRY%3ESHAPES_HC%3EBDD.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT gPPI ANGRY>SHAPES HC>BDD",
+      "points": [], "user": null, "weights": []}, {"conditions": [], "description":
+      "SPM{T_[32.0]} - contrast 3: Int1", "id": "7BtTmQCtTLDG", "images": [{"add_date":
+      "2018-03-25T22:28:25.174486+00:00", "filename": "spmT_gPPI_ANGRY%3ESHAPES_Int1.nii.gz",
+      "id": "4CkksPYhzEVd", "space": "MNI", "url": "http://neurovault.org/media/images/3666/spmT_gPPI_ANGRY%3ESHAPES_Int1.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT gPPI ANGRY>SHAPES Int1", "points":
+      [], "user": null, "weights": []}, {"conditions": [], "description": "SPM{T_[32.0]}
+      - contrast 4: Int2", "id": "5UqTAfa29ak4", "images": [{"add_date": "2018-03-25T22:28:25.604841+00:00",
+      "filename": "spmT_gPPI_ANGRY%3ESHAPES_Int2.nii.gz", "id": "5hnCx2zy4U8k", "space":
+      "MNI", "url": "http://neurovault.org/media/images/3666/spmT_gPPI_ANGRY%3ESHAPES_Int2.nii.gz",
+      "user": null, "value_type": "T"}], "name": "spmT gPPI ANGRY>SHAPES Int2", "points":
+      [], "user": null, "weights": []}], "authors": "Sally A. Grace, Izelle Labuschagne,
+      David J. Castle and Susan L. Rossell", "created_at": "2023-05-20T01:08:26.285482+00:00",
+      "description": "The present study assessed the effects of intranasal oxytocin
+      on the neural basis of processing emotional faces in patients with body dysmorphic
+      disorder (BDD). Twenty BDD patients and 22 matched healthy control participants
+      participated in a randomized, double-blind placebo-controlled within-subject
+      functional magnetic resonance imaging study. Following acute intranasal OXT
+      (24 IU) or placebo administration, we examined group and OXT related differences
+      in task-based amygdala activation and related functional connectivity in response
+      to an emotional face-matching task of fearful, angry, disgusted, sad, surprised
+      and happy faces. ", "doi": "10.1016/j.psyneuen.2019.05.022", "id": "43Tb4A22CFNL",
+      "metadata": {"acquisition_orientation": "", "add_date": "2018-03-24T03:50:11.979230+01:00",
+      "autocorrelation_model": "", "b0_unwarping_software": "", "communities": [],
+      "contributors": "", "coordinate_space": null, "doi_add_date": "2019-05-28T22:49:14.437772+02:00",
+      "download_url": "http://neurovault.org/collections/3666/download", "echo_time":
+      null, "field_of_view": null, "field_strength": null, "flip_angle": null, "full_dataset_url":
+      "", "functional_coregistered_to_structural": null, "functional_coregistration_method":
+      "", "group_comparison": true, "group_description": "", "group_estimation_type":
+      "", "group_inference_type": null, "group_model_multilevel": "", "group_model_type":
+      "", "group_modeling_software": "", "group_repeated_measures": null, "group_repeated_measures_method":
+      "", "handedness": null, "hemodynamic_response_function": "", "high_pass_filter_method":
+      "", "inclusion_exclusion_criteria": "", "interpolation_method": "", "intersubject_registration_software":
+      "", "intersubject_transformation_type": null, "intrasubject_estimation_type":
+      "", "intrasubject_model_type": "", "intrasubject_modeling_software": "", "length_of_blocks":
+      null, "length_of_runs": null, "length_of_trials": "", "matrix_size": null, "modify_date":
+      "2019-05-28T22:49:14.442152+02:00", "motion_correction_interpolation": "", "motion_correction_metric":
+      "", "motion_correction_reference": "", "motion_correction_software": "", "nonlinear_transform_type":
+      "", "number_of_experimental_units": null, "number_of_images": 11, "number_of_imaging_runs":
+      null, "number_of_rejected_subjects": null, "nutbrain_food_choice_type": "",
+      "nutbrain_food_viewing_conditions": "", "nutbrain_hunger_state": null, "nutbrain_odor_conditions":
+      "", "nutbrain_taste_conditions": "", "object_image_type": "", "optimization":
+      null, "optimization_method": "", "order_of_acquisition": null, "order_of_preprocessing_operations":
+      "", "orthogonalization_description": "", "owner": 2051, "owner_name": "sallygrace",
+      "paper_url": "https://linkinghub.elsevier.com/retrieve/pii/S0306453018312241",
+      "parallel_imaging": "", "private": false, "proportion_male_subjects": null,
+      "pulse_sequence": "", "quality_control": "", "repetition_time": null, "resampled_voxel_size":
+      null, "scanner_make": "", "scanner_model": "", "skip_distance": null, "slice_thickness":
+      null, "slice_timing_correction_software": "", "smoothing_fwhm": null, "smoothing_type":
+      "", "software_package": "", "software_version": "", "subject_age_max": null,
+      "subject_age_mean": null, "subject_age_min": null, "target_resolution": null,
+      "target_template_image": "", "transform_similarity_metric": "", "type_of_design":
+      "blocked", "url": "http://neurovault.org/collections/3666/", "used_b0_unwarping":
+      null, "used_dispersion_derivatives": null, "used_high_pass_filter": null, "used_intersubject_registration":
+      null, "used_motion_correction": null, "used_motion_regressors": null, "used_motion_susceptibiity_correction":
+      null, "used_orthogonalization": null, "used_reaction_time_regressor": null,
+      "used_slice_timing_correction": null, "used_smoothing": null, "used_temporal_derivatives":
+      null}, "name": "Intranasal oxytocin alters amygdala-temporal resting-state functional
+      connectivity in body dysmorphic disorder: A double-blind placebo-controlled
+      randomized trial", "pmid": null, "publication": "Psychoneuroendocrinology",
+      "source": "neurovault", "source_id": "3666", "source_updated_at": null, "updated_at":
+      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": null}, {"analyses":
+      [{"conditions": [{"description": null, "id": "3ppM56BG2njM", "name": "monetary
+      incentive delay task", "user": null}], "description": "To test H1, that BPD
+      patients express dysfunctional recruitment of frontal brain regions in response
+      to social (compared to non-social) cues, we directly compared both groups by
+      computing the 2-way interaction \u2018Social Condition\u2019 (social, non-social
+      cues) by \u2018Group\u2019 (HC, BPD).", "id": "6cUpoaBzsSbA", "images": [{"add_date":
+      "2019-10-30T09:14:43.044952+00:00", "filename": "spmT_0008.nii.gz", "id": "7M4uem5dnB6q",
+      "space": "MNI", "url": "http://neurovault.org/media/images/6034/spmT_0008.nii.gz",
+      "user": null, "value_type": "T"}], "name": "Model 1-Cues: Interaction Social
+      Condition by Group", "points": [], "user": null, "weights": [1.0]}, {"conditions":
+      [{"description": null, "id": "3ppM56BG2njM", "name": "monetary incentive delay
+      task", "user": null}], "description": "To test H2, that BPD patients would show
+      impaired amygdala response to social feedback, we conducted ROI analyses (i.e.
+      frontal lobe and amygdala masks) using the 2-way interaction \u2018Group\u2019
+      x \u2018Social Condition\u2019 for the feedback analysis. BPD patients expressed
+      a blunted response of the bilateral amygdala compared to the HCs for the social>non-social
+      feedback contrast. These images show the whole brain images, but the amygdala
+      mask is added in another file.", "id": "4f4dMGS4zuoT", "images": [{"add_date":
+      "2019-10-30T09:28:12.663383+00:00", "filename": "spmT_0017.nii.gz", "id": "7mkeueU7ikKd",
+      "space": "MNI", "url": "http://neurovault.org/media/images/6034/spmT_0017.nii.gz",
+      "user": null, "value_type": "T"}], "name": "Model 2-Feedback: Interaction Social
+      Condition by Group", "points": [], "user": null, "weights": [1.0]}, {"conditions":
+      [{"description": null, "id": "3ppM56BG2njM", "name": "monetary incentive delay
+      task", "user": null}], "description": "Model 3 was created ad hoc in order to
+      test H3 following the outcome of the first two models. We ran a seed-based analysis,
+      using the amygdala feedback-related activity for the negative social (compared
+      to non-social) component of Model 2 as the predictor and testing against potential
+      relationship with cue-evoked signal at a voxel-wise level within Model 1. Specifically,
+      the beta estimates for both groups from the bilateral amygdala ROI for the negative
+      social feedback (i.e. social loss>non-social loss), were extracted from Model
+      2 and entered as a covariate into an independent samples t-test using the specific
+      contrast social>non-social cues. We then tested for the effects of the amygdala
+      covariate in each group separately and compared the differences between the
+      groups. These maps show the differences between groups (i.e. BPD>HC) for this
+      amygdala covariate. ", "id": "7oxFciwfWehs", "images": [{"add_date": "2019-10-30T09:41:58.802747+00:00",
+      "filename": "spmT_0005.nii.gz", "id": "oFWCbNK7eHcN", "space": "MNI", "url":
+      "http://neurovault.org/media/images/6034/spmT_0005.nii.gz", "user": null, "value_type":
+      "T"}], "name": "Model 3--Independent Samples T-Test Regression Analysis", "points":
+      [], "user": null, "weights": [1.0]}, {"conditions": [{"description": null, "id":
+      "3ppM56BG2njM", "name": "monetary incentive delay task", "user": null}], "description":
+      "We utilized a region-of-interest (ROI) analysis approach using the WFU PickAtlas
+      toolbox for SPM8. We created a mask of the bilateral amygdala (used to test
+      H2 in Model 2), from the Talairach Daemon database.", "id": "6skr8EiHiW73",
+      "images": [{"add_date": "2019-10-30T09:51:30.157895+00:00", "filename": "AmyMask.nii.gz",
+      "id": "5H5SUQZcGRv6", "space": "MNI", "url": "http://neurovault.org/media/images/6034/AmyMask.nii.gz",
+      "user": null, "value_type": "ROI/mask"}], "name": "Model 2-Feedback: Amygdala
+      Mask", "points": [], "user": null, "weights": [1.0]}], "authors": "Kimberly
+      C. Doell, Emilie Oli\u00e9, Philippe Courtet, Corrado Corradi-Dell''Acqua, Nader
+      Perroud and Sophie Schwartz", "created_at": "2023-05-20T01:09:51.807961+00:00",
+      "description": "ABSTRACT \r\nBackground- Borderline personality disorder (BPD)
+      is characterized by maladaptive social functioning, and widespread negativity
+      biases. The neural underpinnings of these impairments remain elusive. We thus
+      tested whether BPD patients show atypical neural activity when processing social
+      (compared to non-social) anticipation, feedback, and particularly, how they
+      relate to each other.\r\nMethods- We acquired functional MRI data from 21 BPD
+      women and 24 matched healthy controls (HCs) while they performed a task in which
+      cues and feedbacks were either social (neutral faces for cues; happy or angry
+      faces for positive and negative feedbacks, respectively) or non-social (dollar
+      sign; winning or losing money for positive and negative feedbacks, respectively).
+      This task allowed for the analysis of social anticipatory cues, performance-based
+      feedback, and their interaction. \r\nResults- Compared to HCs, BPD patients
+      expressed increased activation in the superior temporal sulcus during the processing
+      of social cues, consistent with elevated salience associated with an upcoming
+      social event. BPD patients also showed reduced activation in the amygdala while
+      processing evaluative social feedback. Importantly, perigenual anterior cingulate
+      cortex (pgACC) activity during the presentation of the social cue correlated
+      with reduced amygdala activity during the presentation of the negative social
+      feedback in the BPD patients. \r\nConclusions- These neuroimaging results clarify
+      how BPD patients express altered responses to different types of social stimuli
+      (i.e. social anticipatory cues and evaluative feedback) and uncover an atypical
+      relationship between frontolimbic regions (pgACC-amygdala) over the time span
+      of a social interaction. These findings may help to explain why BPD patients
+      suffer from pervasive difficulties adapting their behavior in the context of
+      interpersonal relationships and should be considered while designing better-targeted
+      interventions.", "doi": "10.1016/j.nicl.2019.102126", "id": "5NQYnogUJ2XD",
+      "metadata": {"acquisition_orientation": "", "add_date": "2019-10-30T09:58:20.777993+01:00",
+      "autocorrelation_model": "", "b0_unwarping_software": "", "communities": [],
+      "contributors": "", "coordinate_space": null, "doi_add_date": "2020-01-08T00:02:50.490732+01:00",
+      "download_url": "http://neurovault.org/collections/6034/download", "echo_time":
+      null, "field_of_view": null, "field_strength": null, "flip_angle": null, "full_dataset_url":
+      "", "functional_coregistered_to_structural": null, "functional_coregistration_method":
+      "", "group_comparison": null, "group_description": "", "group_estimation_type":
+      "", "group_inference_type": null, "group_model_multilevel": "", "group_model_type":
+      "", "group_modeling_software": "", "group_repeated_measures": null, "group_repeated_measures_method":
+      "", "handedness": null, "hemodynamic_response_function": "", "high_pass_filter_method":
+      "", "inclusion_exclusion_criteria": "", "interpolation_method": "", "intersubject_registration_software":
+      "", "intersubject_transformation_type": null, "intrasubject_estimation_type":
+      "", "intrasubject_model_type": "", "intrasubject_modeling_software": "", "length_of_blocks":
+      null, "length_of_runs": null, "length_of_trials": "", "matrix_size": null, "modify_date":
+      "2020-01-08T01:43:18.827758+01:00", "motion_correction_interpolation": "", "motion_correction_metric":
+      "", "motion_correction_reference": "", "motion_correction_software": "", "nonlinear_transform_type":
+      "", "number_of_experimental_units": null, "number_of_images": 4, "number_of_imaging_runs":
+      null, "number_of_rejected_subjects": null, "nutbrain_food_choice_type": "",
+      "nutbrain_food_viewing_conditions": "", "nutbrain_hunger_state": null, "nutbrain_odor_conditions":
+      "", "nutbrain_taste_conditions": "", "object_image_type": "", "optimization":
+      null, "optimization_method": "", "order_of_acquisition": null, "order_of_preprocessing_operations":
+      "", "orthogonalization_description": "", "owner": 4432, "owner_name": "doellk",
+      "paper_url": "https://linkinghub.elsevier.com/retrieve/pii/S2213158219304735",
+      "parallel_imaging": "", "private": false, "proportion_male_subjects": null,
+      "pulse_sequence": "", "quality_control": "", "repetition_time": null, "resampled_voxel_size":
+      null, "scanner_make": "", "scanner_model": "", "skip_distance": null, "slice_thickness":
+      null, "slice_timing_correction_software": "", "smoothing_fwhm": null, "smoothing_type":
+      "", "software_package": "", "software_version": "", "subject_age_max": null,
+      "subject_age_mean": null, "subject_age_min": null, "target_resolution": null,
+      "target_template_image": "", "transform_similarity_metric": "", "type_of_design":
+      null, "url": "http://neurovault.org/collections/6034/", "used_b0_unwarping":
+      null, "used_dispersion_derivatives": null, "used_high_pass_filter": null, "used_intersubject_registration":
+      null, "used_motion_correction": null, "used_motion_regressors": null, "used_motion_susceptibiity_correction":
+      null, "used_orthogonalization": null, "used_reaction_time_regressor": null,
+      "used_slice_timing_correction": null, "used_smoothing": null, "used_temporal_derivatives":
+      null}, "name": "Atypical processing of social anticipation and feedback in borderline
+      personality disorder", "pmid": null, "publication": "NeuroImage: Clinical",
+      "source": "neurovault", "source_id": "6034", "source_updated_at": null, "updated_at":
+      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": null}, {"analyses":
+      [{"conditions": [], "description": null, "id": "6HhdbbASwrK3", "images": [],
+      "name": "37588", "points": [{"coordinates": [60.0, -64.0, 28.0], "id": "38c5vf66bcFo",
+      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
+      []}, {"coordinates": [-54.0, -31.0, 10.0], "id": "47dKz73H2HtG", "image": null,
+      "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [-42.0, -58.0, 28.0], "id": "56ypmCsZSSg6", "image": null, "kind": "unknown",
+      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [15.0, -10.0,
+      -20.0], "id": "59D9X9dRgJ7T", "image": null, "kind": "unknown", "label_id":
+      null, "space": "MNI", "values": []}, {"coordinates": [18.0, 11.0, 67.0], "id":
+      "5kFUkxRjSekg", "image": null, "kind": "unknown", "label_id": null, "space":
+      "MNI", "values": []}, {"coordinates": [27.0, -76.0, -29.0], "id": "6AfrXNySoX2m",
+      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
+      []}, {"coordinates": [45.0, 14.0, -35.0], "id": "6iJiNa6Z5PLo", "image": null,
+      "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [42.0, 29.0, -17.0], "id": "7632xo46rTwn", "image": null, "kind": "unknown",
+      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [-51.0, 26.0,
+      -8.0], "id": "7KVqpZTFtAoh", "image": null, "kind": "unknown", "label_id": null,
+      "space": "MNI", "values": []}, {"coordinates": [-3.0, -49.0, 28.0], "id": "7bF2mDaoR8su",
+      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
+      []}, {"coordinates": [18.0, -13.0, -17.0], "id": "Wme5NpZ4TDB9", "image": null,
+      "kind": "unknown", "label_id": null, "space": "MNI", "values": []}, {"coordinates":
+      [-42.0, 14.0, 49.0], "id": "k4kaSWnkAtq3", "image": null, "kind": "unknown",
+      "label_id": null, "space": "MNI", "values": []}], "user": null, "weights": []}],
+      "authors": "Oetken S, Pauly KD, Gur RC, Schneider F, Habel U, Pohl A", "created_at":
+      "2023-05-19T23:38:25.513965+00:00", "description": null, "doi": "10.1016/j.neuropsychologia.2017.04.010",
+      "id": "4rDGfjjGNAgq", "metadata": null, "name": "Don''t worry, be happy - Neural
+      correlates of the influence of musically induced mood on self-evaluation.",
+      "pmid": "28392302", "publication": "Neuropsychologia", "source": "neurosynth",
+      "source_id": "28392302", "source_updated_at": null, "updated_at": "2023-06-21T22:17:27.973390+00:00",
+      "user": null, "year": 2017}, {"analyses": [{"conditions": [], "description":
+      null, "id": "BpS3u6sAfe8g", "images": [], "name": "34402", "points": [{"coordinates":
+      [-14.0, 58.0, 20.0], "id": "3hYiWJPgdtYx", "image": null, "kind": "unknown",
+      "label_id": null, "space": "UNKNOWN", "values": []}, {"coordinates": [-64.0,
+      -24.0, 4.0], "id": "42EdqCTNSZWh", "image": null, "kind": "unknown", "label_id":
+      null, "space": "UNKNOWN", "values": []}, {"coordinates": [-40.0, -26.0, 46.0],
+      "id": "4Mz4JjdsLshS", "image": null, "kind": "unknown", "label_id": null, "space":
+      "UNKNOWN", "values": []}, {"coordinates": [64.0, -18.0, 8.0], "id": "5FLrsYRLP3KC",
+      "image": null, "kind": "unknown", "label_id": null, "space": "UNKNOWN", "values":
+      []}, {"coordinates": [-46.0, -38.0, 10.0], "id": "5Te6suebT6a5", "image": null,
+      "kind": "unknown", "label_id": null, "space": "UNKNOWN", "values": []}, {"coordinates":
+      [-54.0, -20.0, -26.0], "id": "5tUWxj93YP5y", "image": null, "kind": "unknown",
+      "label_id": null, "space": "UNKNOWN", "values": []}, {"coordinates": [14.0,
+      2.0, -16.0], "id": "6igckJsXAvzA", "image": null, "kind": "unknown", "label_id":
+      null, "space": "UNKNOWN", "values": []}, {"coordinates": [8.0, -20.0, 2.0],
+      "id": "7ZBwkAPuqqjY", "image": null, "kind": "unknown", "label_id": null, "space":
+      "UNKNOWN", "values": []}, {"coordinates": [20.0, 50.0, 28.0], "id": "7hF99Fh8yxp2",
+      "image": null, "kind": "unknown", "label_id": null, "space": "UNKNOWN", "values":
+      []}, {"coordinates": [6.0, -2.0, 42.0], "id": "7qJUvYhP9M95", "image": null,
+      "kind": "unknown", "label_id": null, "space": "UNKNOWN", "values": []}, {"coordinates":
+      [22.0, -56.0, 0.0], "id": "hxEqmuCxyEJc", "image": null, "kind": "unknown",
+      "label_id": null, "space": "UNKNOWN", "values": []}, {"coordinates": [16.0,
+      20.0, -12.0], "id": "qFQT6pQkutBW", "image": null, "kind": "unknown", "label_id":
+      null, "space": "UNKNOWN", "values": []}], "user": null, "weights": []}], "authors":
+      "Kong F, Hu S, Wang X, Song Y, Liu J", "created_at": "2023-05-19T23:38:25.513965+00:00",
+      "description": null, "doi": "10.1016/j.neuroimage.2014.11.033", "id": "uPDUNVQUJvpt",
+      "metadata": null, "name": "Neural correlates of the happy life: The amplitude
+      of spontaneous low frequency fluctuations predicts subjective well-being.",
+      "pmid": "25463465", "publication": "NeuroImage", "source": "neurosynth", "source_id":
+      "25463465", "source_updated_at": null, "updated_at": "2023-06-21T22:17:27.973390+00:00",
+      "user": null, "year": 2015}, {"analyses": [{"conditions": [], "description":
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+      "64zmKUPQ7YmC", "image": null, "kind": "unknown", "label_id": null, "space":
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+      "image": null, "kind": "unknown", "label_id": null, "space": "TAL", "values":
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+      "kind": "unknown", "label_id": null, "space": "TAL", "values": []}, {"coordinates":
+      [28.0, -36.0, 52.0], "id": "6hFiW9BMZUGx", "image": null, "kind": "unknown",
+      "label_id": null, "space": "TAL", "values": []}, {"coordinates": [-39.0, -2.0,
+      3.0], "id": "6o2qc8u43wgu", "image": null, "kind": "unknown", "label_id": null,
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+      "image": null, "kind": "unknown", "label_id": null, "space": "TAL", "values":
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+      [-22.0, -16.0, 25.0], "id": "87gKXQHczUJN", "image": null, "kind": "unknown",
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+      "space": "TAL", "values": []}], "user": null, "weights": []}, {"conditions":
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+      "label_id": null, "space": "TAL", "values": []}, {"coordinates": [14.0, -19.0,
+      67.0], "id": "7YAT4LuC6gog", "image": null, "kind": "unknown", "label_id": null,
+      "space": "TAL", "values": []}, {"coordinates": [-11.0, -26.0, 65.0], "id": "7bwnED5VnhKT",
+      "image": null, "kind": "unknown", "label_id": null, "space": "TAL", "values":
+      []}, {"coordinates": [65.0, -37.0, -6.0], "id": "7sJwXron7cSD", "image": null,
+      "kind": "unknown", "label_id": null, "space": "TAL", "values": []}, {"coordinates":
+      [-34.0, -27.0, -23.0], "id": "89XBCHw62moC", "image": null, "kind": "unknown",
+      "label_id": null, "space": "TAL", "values": []}], "user": null, "weights": []}],
+      "authors": "Egidi G, Caramazza A", "created_at": "2023-05-19T23:38:25.513965+00:00",
+      "description": null, "doi": "10.1016/j.neuroimage.2014.09.008", "id": "6SoirEH52CMp",
+      "metadata": null, "name": "Mood-dependent integration in discourse comprehension:
+      happy and sad moods affect consistency processing via different brain networks.",
+      "pmid": "25225000", "publication": "NeuroImage", "source": "neurosynth", "source_id":
+      "25225000", "source_updated_at": null, "updated_at": "2023-06-21T22:17:27.973390+00:00",
+      "user": null, "year": 2014}, {"analyses": [{"conditions": [], "description":
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+      Date:
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+      Server:
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diff --git a/compose_runner/tests/cassettes/test_run/test_run_workflow.yaml b/compose_runner/tests/cassettes/test_run/test_run_workflow.yaml
new file mode 100644
index 0000000..11cb258
--- /dev/null
+++ b/compose_runner/tests/cassettes/test_run/test_run_workflow.yaml
@@ -0,0 +1,46547 @@
+interactions:
+- request:
+    body: null
+    headers:
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+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      User-Agent:
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+        0l1CKzVetWmxnGRU2z/qSEVU3VoBd+t4dRNfDxXrKu29HBFrwQ1osMNsCjOFmcL8K0z3vpir8AfV
+        0MC7UpWMXLe/V04pMpdUzO1vlHT1ebLMpn6LWgfrCxwTuFWwBQAA
+    headers:
+      Access-Control-Allow-Origin:
+      - '*'
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 23 Nov 2023 00:04:32 GMT
+      Server:
+      - nginx/1.21.6
+      Strict-Transport-Security:
+      - max-age=31536000
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Accept-Encoding
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/compose_runner/tests/test_run.py b/compose_runner/tests/test_run.py
new file mode 100644
index 0000000..6413261
--- /dev/null
+++ b/compose_runner/tests/test_run.py
@@ -0,0 +1,56 @@
+import pytest
+from compose_runner.run import Runner
+
+
+@pytest.mark.vcr(record_mode="once")
+def test_download_bundle():
+    runner = Runner(
+        meta_analysis_id="3opENJpHxRsH",
+        environment="staging",
+    )
+    runner.download_bundle()
+    assert runner.cached_studyset is not None
+    assert runner.cached_annotation is not None
+    assert runner.cached_specification is not None
+
+
+@pytest.mark.vcr(record_mode="once")
+def test_run_workflow():
+    runner = Runner(
+        meta_analysis_id="3opENJpHxRsH",
+        environment="staging",
+    )
+    runner.run_workflow()
+
+
+@pytest.mark.vcr(record_mode="once")
+def test_run_database_workflow():
+    runner = Runner(
+        meta_analysis_id="dRFtnAo9bhp3",
+        environment="staging",
+    )
+    runner.run_workflow()
+
+
+@pytest.mark.vcr(record_mode="once")
+def test_run_group_comparison_workflow():
+    runner = Runner(
+        meta_analysis_id="4CGQSSyaoWN3",
+        environment="staging",
+    )
+    runner.run_workflow()
+
+
+@pytest.mark.vcr(record_mode="once")
+def test_run_string_group_comparison_workflow():
+    runner = Runner(
+        meta_analysis_id="7joU2Siajs5X",
+        environment="staging",
+    )
+    runner.run_workflow()
+
+# def test_yifan_workflow():
+#     runner = Runner(
+#         meta_analysis_id="4WELjap2yCJm",
+#     )
+#     runner.run_workflow()
diff --git a/pyproject.toml b/pyproject.toml
index a61d0f2..b97e9cd 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,7 +17,7 @@ dynamic = ["version"]
 dependencies = ["nimare==0.2.0", "click"]
 
 [project.urls]
-Repository = "https://github.com/neurostuff/nsc-runner"
+Repository = "https://github.com/neurostuff/compose-runner"
 
 [project.optional-dependencies]
 tests = [
@@ -27,18 +27,17 @@ tests = [
 ]
 
 [project.scripts]
-compose-run = "pynsc.cli:cli"
+compose-run = "compose_runner.cli:cli"
 
 [tool.hatch.version]
 source = "vcs"
 
 [tool.hatch.build.hooks.vcs]
-version-file = "pynsc/_version.py"
+version-file = "compose_runner/_version.py"
 
 [tool.hatch.build]
 exclude = [
   "/.*",
-  "pynsc/tests",
 ]
 
 [tool.flake8]

From daf093108fc5d7e22f9e9299efabcce7f1439d4c Mon Sep 17 00:00:00 2001
From: James Kent <jamesdkent21@gmail.com>
Date: Fri, 22 Dec 2023 10:56:16 -0600
Subject: [PATCH 2/3] remove pycache

---
 .../__pycache__/__init__.cpython-38.pyc          | Bin 141 -> 0 bytes
 compose_runner/__pycache__/run.cpython-38.pyc    | Bin 9889 -> 0 bytes
 .../tests/__pycache__/__init__.cpython-38.pyc    | Bin 147 -> 0 bytes
 .../test_run.cpython-38-pytest-7.4.3.pyc         | Bin 2339 -> 0 bytes
 4 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 compose_runner/__pycache__/__init__.cpython-38.pyc
 delete mode 100644 compose_runner/__pycache__/run.cpython-38.pyc
 delete mode 100644 compose_runner/tests/__pycache__/__init__.cpython-38.pyc
 delete mode 100644 compose_runner/tests/__pycache__/test_run.cpython-38-pytest-7.4.3.pyc

diff --git a/compose_runner/__pycache__/__init__.cpython-38.pyc b/compose_runner/__pycache__/__init__.cpython-38.pyc
deleted file mode 100644
index 4290fd94d543de0eba1b13e05f95dae1491b0399..0000000000000000000000000000000000000000
GIT binary patch
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From 404287bea1a71b0e87e33754b0eadbad62f0dbde Mon Sep 17 00:00:00 2001
From: James Kent <jamesdkent21@gmail.com>
Date: Fri, 22 Dec 2023 10:57:01 -0600
Subject: [PATCH 3/3] rename old files

---
 pynsc/__init__.py                             |      0
 pynsc/cli.py                                  |     25 -
 pynsc/run.py                                  |    421 -
 pynsc/tests/__init__.py                       |      0
 .../test_run/test_download_bundle.yaml        |    964 -
 .../test_run/test_run_database_workflow.yaml  | 104965 ---------------
 .../test_run_group_comparison_workflow.yaml   |  48633 -------
 ..._run_string_group_comparison_workflow.yaml |  41538 ------
 .../cassettes/test_run/test_run_workflow.yaml |  46547 -------
 pynsc/tests/test_run.py                       |     56 -
 10 files changed, 243149 deletions(-)
 delete mode 100644 pynsc/__init__.py
 delete mode 100644 pynsc/cli.py
 delete mode 100644 pynsc/run.py
 delete mode 100644 pynsc/tests/__init__.py
 delete mode 100644 pynsc/tests/cassettes/test_run/test_download_bundle.yaml
 delete mode 100644 pynsc/tests/cassettes/test_run/test_run_database_workflow.yaml
 delete mode 100644 pynsc/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
 delete mode 100644 pynsc/tests/cassettes/test_run/test_run_string_group_comparison_workflow.yaml
 delete mode 100644 pynsc/tests/cassettes/test_run/test_run_workflow.yaml
 delete mode 100644 pynsc/tests/test_run.py

diff --git a/pynsc/__init__.py b/pynsc/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/pynsc/cli.py b/pynsc/cli.py
deleted file mode 100644
index 60a37b2..0000000
--- a/pynsc/cli.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import click
-
-from pynsc.run import run
-
-
-@click.command()
-@click.argument("meta-analysis-id", required=True)
-@click.option("--result-dir", help="The directory to save results to.")
-@click.option(
-    "environment",
-    "--environment",
-    type=click.Choice(["production", "staging", "local"], case_sensitive=False),
-    default="production",
-    help="DEVELOPER USE ONLY Use another server instead of production server.",
-)
-@click.option("nsc_key", "--nsc-key", help="Neurosynth Compose api key.")
-@click.option("nv_key", "--nv-key", help="Neurovault api key.")
-@click.option("--no-upload", is_flag=True, help="Do not upload results.")
-def cli(meta_analysis_id, environment, result_dir, nsc_key, nv_key, no_upload):
-    """Execute and upload a meta-analysis workflow.
-
-    META_ANALYSIS_ID is the id of the meta-analysis on neurosynth-compose.
-    """
-    url, _ = run(meta_analysis_id, environment, result_dir, nsc_key, nv_key, no_upload)
-    print(url)
diff --git a/pynsc/run.py b/pynsc/run.py
deleted file mode 100644
index 341f428..0000000
--- a/pynsc/run.py
+++ /dev/null
@@ -1,421 +0,0 @@
-from importlib import import_module
-from pathlib import Path
-import gzip
-import json
-import io
-
-import requests
-
-# import neurosynth_compose_sdk
-# from neurosynth_compose_sdk.api.compose_api import ComposeApi
-# import neurostore_sdk
-# from neurostore_sdk.api.store_api import StoreApi
-from nimare.workflows import CBMAWorkflow, PairwiseCBMAWorkflow
-from nimare.meta.cbma.base import CBMAEstimator, PairwiseCBMAEstimator
-from nimare.nimads import Studyset, Annotation
-from nimare.meta.cbma import ALE, ALESubtraction, SCALE
-
-
-def gen_database_url(branch, database):
-    return f"https://github.com/neurostuff/neurostore_database/raw/{branch}/{database}.json.gz"
-
-
-class Runner:
-    """Runner for executing and uploading a meta-analysis workflow."""
-
-    def __init__(
-        self,
-        meta_analysis_id,
-        environment="production",
-        result_dir=None,
-        nsc_key=None,
-        nv_key=None,
-    ):
-        # the meta-analysis id associated with this run
-        self.meta_analysis_id = meta_analysis_id
-
-        if environment == "staging":
-            # staging
-            self.compose_url = "https://synth.neurostore.xyz/api"
-            self.store_url = "https://neurostore.xyz/api"
-            self.reference_studysets = {
-                "neurosynth": gen_database_url("staging", "neurosynth"),
-                "neuroquery": gen_database_url("staging", "neuroquery"),
-                "neurostore": gen_database_url("staging", "neurostore"),
-                "neurostore_small": gen_database_url("staging", "neurostore_small"),
-            }
-        elif environment == "local":
-            self.compose_url = "http://localhost:81/api"
-            self.store_url = "http://localhost:80/api"
-            self.reference_studysets = {
-                "neurosynth": gen_database_url("staging", "neurosynth"),
-                "neuroquery": gen_database_url("staging", "neuroquery"),
-                "neurostore": gen_database_url("staging", "neurostore"),
-                "neurostore_small": gen_database_url("staging", "neurostore_small"),
-            }
-        else:
-            # production
-            self.compose_url = "https://compose.neurosynth.org/api"
-            self.store_url = "https://neurostore.org/api"
-            self.reference_studysets = {
-                "neurosynth": gen_database_url("main", "neurosynth"),
-                "neuroquery": gen_database_url("main", "neuroquery"),
-                "neurostore": gen_database_url("main", "neurostore"),
-            }
-
-        # Enter a context with an instance of the API client
-        # compose_configuration = neurosynth_compose_sdk.Configuration(
-        #     host=self.compose_url
-        # )
-        # store_configuration = neurostore_sdk.Configuration(host=self.store_url)
-        # compose_client = neurosynth_compose_sdk.ApiClient(compose_configuration)
-        # store_client = neurostore_sdk.ApiClient(store_configuration)
-        # self.compose_api = ComposeApi(compose_client)
-        # self.store_api = StoreApi(store_client)
-
-        # initialize inputs
-        self.cached_studyset = None
-        self.cached_annotation = None
-        self.cached_specification = None
-        self.first_dataset = None
-        self.second_dataset = None
-        self.estimator = None
-        self.corrector = None
-
-        # initialize api-keys
-        self.nsc_key = nsc_key  # neurosynth compose key to upload to neurosynth compose
-        self.nv_key = nv_key  # neurovault key to upload to neurovault
-
-        # result directory
-        if result_dir is None:
-            self.result_dir = Path.cwd() / "results"
-        else:
-            self.result_dir = Path(result_dir)
-
-        # whether the inputs were cached from neurostore
-        self.cached = True
-
-        # initialize outputs
-        self.result_id = None
-        self.meta_results = None  # the meta-analysis result output from nimare
-        self.results_object = (
-            None  # the result object represented on neurosynth compose
-        )
-
-    def run_workflow(self, no_upload=False):
-        self.download_bundle()
-        self.process_bundle()
-        self.run_meta_analysis()
-        if not no_upload:
-            self.create_result_object()
-            self.upload_results()
-
-    def download_bundle(self):
-        meta_analysis = requests.get(
-            f"{self.compose_url}/meta-analyses/{self.meta_analysis_id}?nested=true"
-        ).json()
-        # meta_analysis = self.compose_api.meta_analyses_id_get(
-        #     id=self.meta_analysis_id, nested=True
-        # ).to_dict()  # does not currently return run_key
-
-        # check to see if studyset and annotation are cached
-        studyset_dict = annotation_dict = None
-        if meta_analysis["studyset"]:
-            studyset_dict = meta_analysis["studyset"]["snapshot"]
-            self.cached_studyset = (
-                None if studyset_dict is None else studyset_dict.get("snapshot", None)
-            )
-        if meta_analysis["annotation"]:
-            annotation_dict = meta_analysis["annotation"]["snapshot"]
-            self.cached_annotation = (
-                None
-                if annotation_dict is None
-                else annotation_dict.get("snapshot", None)
-            )
-        # if either are not cached, download them from neurostore
-        if self.cached_studyset is None or self.cached_annotation is None:
-            self.cached_studyset = requests.get(
-                (
-                    f"{self.store_url}/studysets/"
-                    f"{meta_analysis['studyset']['neurostore_id']}?nested=true"
-                )
-            ).json()
-            self.cached_annotation = requests.get(
-                f"{self.store_url}/annotations/{meta_analysis['annotation']['neurostore_id']}"
-            ).json()
-            # set cached to false
-            self.cached = False
-        # retrieve specification
-        self.cached_specification = meta_analysis["specification"]
-
-        # run key for running this particular meta-analysis
-        self.nsc_key = meta_analysis["run_key"]
-
-    def apply_filter(self, studyset, annotation):
-        """
-        Apply filter to studyset.
-            Options:
-                - bool: filter by boolean column
-                  can be single or multiple conditions
-                - string: filter by string column
-                  can be single or multiple conditions
-                - database_studyset: use a reference studyset
-                  only useful for multiple conditions
-        """
-        column = self.cached_specification["filter"]
-        column_type = self.cached_annotation["note_keys"][f"{column}"]
-        conditions = self.cached_specification.get("conditions", [])
-        database_studyset = self.cached_specification.get("database_studyset")
-        weights = self.cached_specification.get("weights", [])
-        weight_conditions = {w: c for c, w in zip(conditions, weights)}
-
-        if not (conditions or weights) and column_type != "boolean":
-            raise ValueError(
-                f"Column type {column_type} requires a conditions and weights."
-            )
-
-        # get analysis ids for the first studyset
-        if column_type == "boolean":
-            analysis_ids = [
-                n.analysis.id for n in annotation.notes if n.note[f"{column}"]
-            ]
-
-        elif column_type == "string":
-            analysis_ids = [
-                n.analysis.id
-                for n in annotation.notes
-                if n.note[f"{column}"] == weight_conditions[1]
-            ]
-        else:
-            raise ValueError(f"Column type {column_type} not supported.")
-
-        first_studyset = studyset.slice(analyses=analysis_ids)
-        first_studyset = first_studyset.combine_analyses()
-
-        # if there is only one condition, return the first studyset
-        if len(conditions) <= 1 and not database_studyset:
-            return first_studyset, None
-
-        elif len(conditions) == 2 and database_studyset:
-            raise ValueError("Cannot have multiple conditions and a database studyset.")
-
-        elif len(conditions) == 2 and not database_studyset:
-            second_analysis_ids = [
-                n.analysis.id
-                for n in annotation.notes
-                if n.note[f"{column}"] == weight_conditions[-1]
-            ]
-            second_studyset = studyset.slice(analyses=second_analysis_ids)
-            second_studyset = second_studyset.combine_analyses()
-
-            return first_studyset, second_studyset
-
-        elif len(conditions) <= 1 and database_studyset:
-            # Download the gzip file
-            response = requests.get(self.reference_studysets[database_studyset])
-
-            # Check if the request was successful
-            if response.status_code != 200:
-                raise ValueError(
-                    f"Could not download reference studyset {database_studyset}."
-                )
-            # Wrap the content of the response in a BytesIO object
-            gzip_content = io.BytesIO(response.content)
-
-            # Decompress the gzip content
-            with gzip.GzipFile(fileobj=gzip_content, mode="rb") as gz_file:
-                # Read and decode the JSON data
-                json_data = gz_file.read().decode("utf-8")
-
-                # Load the JSON data into a dictionary
-                reference_studyset_dict = json.loads(json_data)
-
-            reference_studyset = Studyset(reference_studyset_dict)
-
-            # get study ids from studyset
-            study_ids = set([s.id for s in studyset.studies])
-
-            # reference study ids
-            reference_study_ids = set([s.id for s in reference_studyset.studies])
-
-            keep_study_ids = reference_study_ids - study_ids
-
-            # get analysis ids from reference studyset
-            analysis_ids = [
-                a.id
-                for s in reference_studyset.studies
-                for a in s.analyses
-                if s.id in keep_study_ids
-            ]
-            second_studyset = reference_studyset.slice(analyses=analysis_ids)
-            second_studyset = second_studyset.combine_analyses()
-
-            return first_studyset, second_studyset
-
-    def process_bundle(self):
-        studyset = Studyset(self.cached_studyset)
-        annotation = Annotation(self.cached_annotation, studyset)
-        first_studyset, second_studyset = self.apply_filter(studyset, annotation)
-        first_dataset = first_studyset.to_dataset()
-        second_dataset = (
-            second_studyset.to_dataset() if second_studyset is not None else None
-        )
-        estimator, corrector = self.load_specification()
-        estimator, corrector = self.validate_specification(
-            estimator, corrector, first_dataset, second_dataset
-        )
-        self.first_dataset = first_dataset
-        self.second_dataset = second_dataset
-        self.estimator = estimator
-        self.corrector = corrector
-
-    def create_result_object(self):
-        # take a snapshot of the studyset and annotation (before running the workflow)
-        headers = {"Compose-Upload-Key": self.nsc_key}
-        data = {"meta_analysis_id": self.meta_analysis_id}
-        if not self.cached:
-            data.update(
-                {
-                    "studyset_snapshot": self.cached_studyset,
-                    "annotation_snapshot": self.cached_annotation,
-                }
-            )
-        resp = requests.post(
-            f"{self.compose_url}/meta-analysis-results",
-            json=data,
-            headers=headers,
-        )
-        self.result_id = resp.json().get("id", None)
-        if self.result_id is None:
-            raise ValueError(f"Could not create result for {self.meta_analysis_id}")
-
-    def run_meta_analysis(self):
-        if self.second_dataset and isinstance(self.estimator, PairwiseCBMAEstimator):
-            workflow = PairwiseCBMAWorkflow(
-                estimator=self.estimator,
-                corrector=self.corrector,
-                diagnostics="focuscounter",
-                output_dir=self.result_dir,
-            )
-            self.meta_results = workflow.fit(self.first_dataset, self.second_dataset)
-        elif self.second_dataset is None and isinstance(self.estimator, CBMAEstimator):
-            workflow = CBMAWorkflow(
-                estimator=self.estimator,
-                corrector=self.corrector,
-                diagnostics="focuscounter",
-                output_dir=self.result_dir,
-            )
-            self.meta_results = workflow.fit(self.first_dataset, self.second_dataset)
-        else:
-            raise ValueError(
-                f"Estimator {self.estimator} and datasets {self.first_dataset} and {self.second_dataset} are not compatible."
-            )
-
-    def upload_results(self):
-        statistical_maps = [
-            (
-                "statistical_maps",
-                open(self.result_dir / (m + ".nii.gz"), "rb"),
-            )
-            for m in self.meta_results.maps.keys()
-            if not m.startswith("label_")
-        ]
-        cluster_tables = [
-            (
-                "cluster_tables",
-                open(self.result_dir / (f + ".tsv"), "rb"),
-            )
-            for f, df in self.meta_results.tables.items()
-            if "clust" in f and not df.empty
-        ]
-
-        diagnostic_tables = [
-            (
-                "diagnostic_tables",
-                open(self.result_dir / (f + ".tsv"), "rb"),
-            )
-            for f, df in self.meta_results.tables.items()
-            if "clust" not in f and df is not None
-        ]
-        files = statistical_maps + cluster_tables + diagnostic_tables
-
-        headers = {"Compose-Upload-Key": self.nsc_key}
-        self.results_object = requests.put(
-            f"{self.compose_url}/meta-analysis-results/{self.result_id}",
-            files=files,
-            json={"method_description": self.meta_results.description_},
-            headers=headers,
-        )
-
-    def load_specification(self):
-        """Returns function to run analysis on dataset."""
-        spec = self.cached_specification
-        est_mod = import_module(".".join(["nimare", "meta", spec["type"].lower()]))
-        estimator = getattr(est_mod, spec["estimator"]["type"])
-        if spec["estimator"].get("args"):
-            est_args = {**spec["estimator"]["args"]}
-            if est_args.get("**kwargs") is not None:
-                for k, v in est_args["**kwargs"].items():
-                    est_args[k] = v
-                del est_args["**kwargs"]
-            estimator_init = estimator(**est_args)
-        else:
-            estimator_init = estimator()
-
-        if spec.get("corrector"):
-            cor_mod = import_module(".".join(["nimare", "correct"]))
-            corrector = getattr(cor_mod, spec["corrector"]["type"])
-            if spec["corrector"].get("args"):
-                cor_args = {**spec["corrector"]["args"]}
-                if cor_args.get("**kwargs") is not None:
-                    for k, v in cor_args["**kwargs"].items():
-                        cor_args[k] = v
-                    del cor_args["**kwargs"]
-                corrector_init = corrector(**cor_args)
-            else:
-                corrector_init = corrector()
-        else:
-            corrector_init = None
-
-        return estimator_init, corrector_init
-
-    def validate_specification(
-        self, estimator, corrector, dataset, second_dataset=None
-    ):
-        if (
-            isinstance(estimator, (ALE, ALESubtraction, SCALE))
-            and estimator.kernel_transformer.sample_size is not None
-        ):
-            if any(dataset.metadata["sample_sizes"].isnull()):
-                raise ValueError(
-                    "Sample size is required for ALE with sample size weighting."
-                )
-        return estimator, corrector
-
-
-def run(
-    meta_analysis_id,
-    environment="production",
-    result_dir=None,
-    nsc_key=None,
-    nv_key=None,
-    no_upload=False,
-):
-    runner = Runner(
-        meta_analysis_id=meta_analysis_id,
-        environment=environment,
-        result_dir=result_dir,
-        nsc_key=nsc_key,
-        nv_key=nv_key,
-    )
-
-    runner.run_workflow(no_upload=no_upload)
-
-    if no_upload:
-        return None, runner.meta_results
-
-    url = "/".join(
-        [runner.compose_url.rstrip("/api"), "meta-analyses", meta_analysis_id]
-    )
-
-    return url, runner.meta_results
diff --git a/pynsc/tests/__init__.py b/pynsc/tests/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/pynsc/tests/cassettes/test_run/test_download_bundle.yaml b/pynsc/tests/cassettes/test_run/test_download_bundle.yaml
deleted file mode 100644
index 0e0078d..0000000
--- a/pynsc/tests/cassettes/test_run/test_download_bundle.yaml
+++ /dev/null
@@ -1,964 +0,0 @@
-interactions:
-- request:
-    body: null
-    headers:
-      Accept:
-      - '*/*'
-      Accept-Encoding:
-      - gzip, deflate
-      Connection:
-      - keep-alive
-      User-Agent:
-      - python-requests/2.28.2
-    method: GET
-    uri: https://synth.neurostore.xyz/api/meta-analyses/3opENJpHxRsH?nested=true
-  response:
-    body:
-      string: !!binary |
-        H4sIAAAAAAAAA+y9WZfquJao+16/wiNeTu1zgkhw7/Wwa9CTdEnfnXtHDmPL2IAb3NDVrf9+ZUOs
-        CBoL0skCTMpVYycLKWwjzU+ampqa87//gyDeRMMwXdHVTOPtB/Hf8Bv4nWQD0QXyn6ILv3sjkySV
-        SDIJkuqQyR+08INhPpIUTwnU/0kmfySTb++7v9Jkv/bIpDOz7jQr0K7xWWIAzzYd17TBn7tKTLth
-        NZZDai0UrM9KjiFajmq6P1/j/HcXXi/F/EjRH0k2SXHkwesFfykDR7I1a/9r374Xhb5YUKoDV5RF
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diff --git a/pynsc/tests/cassettes/test_run/test_run_database_workflow.yaml b/pynsc/tests/cassettes/test_run/test_run_database_workflow.yaml
deleted file mode 100644
index de28ee5..0000000
--- a/pynsc/tests/cassettes/test_run/test_run_database_workflow.yaml
+++ /dev/null
@@ -1,104965 +0,0 @@
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-- request:
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-      Accept-Encoding:
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diff --git a/pynsc/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml b/pynsc/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
deleted file mode 100644
index 9708bb8..0000000
--- a/pynsc/tests/cassettes/test_run/test_run_group_comparison_workflow.yaml
+++ /dev/null
@@ -1,48633 +0,0 @@
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-      "blocked", "url": "http://neurovault.org/collections/3666/", "used_b0_unwarping":
-      null, "used_dispersion_derivatives": null, "used_high_pass_filter": null, "used_intersubject_registration":
-      null, "used_motion_correction": null, "used_motion_regressors": null, "used_motion_susceptibiity_correction":
-      null, "used_orthogonalization": null, "used_reaction_time_regressor": null,
-      "used_slice_timing_correction": null, "used_smoothing": null, "used_temporal_derivatives":
-      null}, "name": "Intranasal oxytocin alters amygdala-temporal resting-state functional
-      connectivity in body dysmorphic disorder: A double-blind placebo-controlled
-      randomized trial", "pmid": null, "publication": "Psychoneuroendocrinology",
-      "source": "neurovault", "source_id": "3666", "source_updated_at": null, "updated_at":
-      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": null}, {"analyses":
-      [{"conditions": [{"description": null, "id": "3ppM56BG2njM", "name": "monetary
-      incentive delay task", "user": null}], "description": "To test H1, that BPD
-      patients express dysfunctional recruitment of frontal brain regions in response
-      to social (compared to non-social) cues, we directly compared both groups by
-      computing the 2-way interaction \u2018Social Condition\u2019 (social, non-social
-      cues) by \u2018Group\u2019 (HC, BPD).", "id": "6cUpoaBzsSbA", "images": [{"add_date":
-      "2019-10-30T09:14:43.044952+00:00", "filename": "spmT_0008.nii.gz", "id": "7M4uem5dnB6q",
-      "space": "MNI", "url": "http://neurovault.org/media/images/6034/spmT_0008.nii.gz",
-      "user": null, "value_type": "T"}], "name": "Model 1-Cues: Interaction Social
-      Condition by Group", "points": [], "user": null, "weights": [1.0]}, {"conditions":
-      [{"description": null, "id": "3ppM56BG2njM", "name": "monetary incentive delay
-      task", "user": null}], "description": "To test H2, that BPD patients would show
-      impaired amygdala response to social feedback, we conducted ROI analyses (i.e.
-      frontal lobe and amygdala masks) using the 2-way interaction \u2018Group\u2019
-      x \u2018Social Condition\u2019 for the feedback analysis. BPD patients expressed
-      a blunted response of the bilateral amygdala compared to the HCs for the social>non-social
-      feedback contrast. These images show the whole brain images, but the amygdala
-      mask is added in another file.", "id": "4f4dMGS4zuoT", "images": [{"add_date":
-      "2019-10-30T09:28:12.663383+00:00", "filename": "spmT_0017.nii.gz", "id": "7mkeueU7ikKd",
-      "space": "MNI", "url": "http://neurovault.org/media/images/6034/spmT_0017.nii.gz",
-      "user": null, "value_type": "T"}], "name": "Model 2-Feedback: Interaction Social
-      Condition by Group", "points": [], "user": null, "weights": [1.0]}, {"conditions":
-      [{"description": null, "id": "3ppM56BG2njM", "name": "monetary incentive delay
-      task", "user": null}], "description": "Model 3 was created ad hoc in order to
-      test H3 following the outcome of the first two models. We ran a seed-based analysis,
-      using the amygdala feedback-related activity for the negative social (compared
-      to non-social) component of Model 2 as the predictor and testing against potential
-      relationship with cue-evoked signal at a voxel-wise level within Model 1. Specifically,
-      the beta estimates for both groups from the bilateral amygdala ROI for the negative
-      social feedback (i.e. social loss>non-social loss), were extracted from Model
-      2 and entered as a covariate into an independent samples t-test using the specific
-      contrast social>non-social cues. We then tested for the effects of the amygdala
-      covariate in each group separately and compared the differences between the
-      groups. These maps show the differences between groups (i.e. BPD>HC) for this
-      amygdala covariate. ", "id": "7oxFciwfWehs", "images": [{"add_date": "2019-10-30T09:41:58.802747+00:00",
-      "filename": "spmT_0005.nii.gz", "id": "oFWCbNK7eHcN", "space": "MNI", "url":
-      "http://neurovault.org/media/images/6034/spmT_0005.nii.gz", "user": null, "value_type":
-      "T"}], "name": "Model 3--Independent Samples T-Test Regression Analysis", "points":
-      [], "user": null, "weights": [1.0]}, {"conditions": [{"description": null, "id":
-      "3ppM56BG2njM", "name": "monetary incentive delay task", "user": null}], "description":
-      "We utilized a region-of-interest (ROI) analysis approach using the WFU PickAtlas
-      toolbox for SPM8. We created a mask of the bilateral amygdala (used to test
-      H2 in Model 2), from the Talairach Daemon database.", "id": "6skr8EiHiW73",
-      "images": [{"add_date": "2019-10-30T09:51:30.157895+00:00", "filename": "AmyMask.nii.gz",
-      "id": "5H5SUQZcGRv6", "space": "MNI", "url": "http://neurovault.org/media/images/6034/AmyMask.nii.gz",
-      "user": null, "value_type": "ROI/mask"}], "name": "Model 2-Feedback: Amygdala
-      Mask", "points": [], "user": null, "weights": [1.0]}], "authors": "Kimberly
-      C. Doell, Emilie Oli\u00e9, Philippe Courtet, Corrado Corradi-Dell''Acqua, Nader
-      Perroud and Sophie Schwartz", "created_at": "2023-05-20T01:09:51.807961+00:00",
-      "description": "ABSTRACT \r\nBackground- Borderline personality disorder (BPD)
-      is characterized by maladaptive social functioning, and widespread negativity
-      biases. The neural underpinnings of these impairments remain elusive. We thus
-      tested whether BPD patients show atypical neural activity when processing social
-      (compared to non-social) anticipation, feedback, and particularly, how they
-      relate to each other.\r\nMethods- We acquired functional MRI data from 21 BPD
-      women and 24 matched healthy controls (HCs) while they performed a task in which
-      cues and feedbacks were either social (neutral faces for cues; happy or angry
-      faces for positive and negative feedbacks, respectively) or non-social (dollar
-      sign; winning or losing money for positive and negative feedbacks, respectively).
-      This task allowed for the analysis of social anticipatory cues, performance-based
-      feedback, and their interaction. \r\nResults- Compared to HCs, BPD patients
-      expressed increased activation in the superior temporal sulcus during the processing
-      of social cues, consistent with elevated salience associated with an upcoming
-      social event. BPD patients also showed reduced activation in the amygdala while
-      processing evaluative social feedback. Importantly, perigenual anterior cingulate
-      cortex (pgACC) activity during the presentation of the social cue correlated
-      with reduced amygdala activity during the presentation of the negative social
-      feedback in the BPD patients. \r\nConclusions- These neuroimaging results clarify
-      how BPD patients express altered responses to different types of social stimuli
-      (i.e. social anticipatory cues and evaluative feedback) and uncover an atypical
-      relationship between frontolimbic regions (pgACC-amygdala) over the time span
-      of a social interaction. These findings may help to explain why BPD patients
-      suffer from pervasive difficulties adapting their behavior in the context of
-      interpersonal relationships and should be considered while designing better-targeted
-      interventions.", "doi": "10.1016/j.nicl.2019.102126", "id": "5NQYnogUJ2XD",
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-      "autocorrelation_model": "", "b0_unwarping_software": "", "communities": [],
-      "contributors": "", "coordinate_space": null, "doi_add_date": "2020-01-08T00:02:50.490732+01:00",
-      "download_url": "http://neurovault.org/collections/6034/download", "echo_time":
-      null, "field_of_view": null, "field_strength": null, "flip_angle": null, "full_dataset_url":
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-      "", "group_comparison": null, "group_description": "", "group_estimation_type":
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-      "", "handedness": null, "hemodynamic_response_function": "", "high_pass_filter_method":
-      "", "inclusion_exclusion_criteria": "", "interpolation_method": "", "intersubject_registration_software":
-      "", "intersubject_transformation_type": null, "intrasubject_estimation_type":
-      "", "intrasubject_model_type": "", "intrasubject_modeling_software": "", "length_of_blocks":
-      null, "length_of_runs": null, "length_of_trials": "", "matrix_size": null, "modify_date":
-      "2020-01-08T01:43:18.827758+01:00", "motion_correction_interpolation": "", "motion_correction_metric":
-      "", "motion_correction_reference": "", "motion_correction_software": "", "nonlinear_transform_type":
-      "", "number_of_experimental_units": null, "number_of_images": 4, "number_of_imaging_runs":
-      null, "number_of_rejected_subjects": null, "nutbrain_food_choice_type": "",
-      "nutbrain_food_viewing_conditions": "", "nutbrain_hunger_state": null, "nutbrain_odor_conditions":
-      "", "nutbrain_taste_conditions": "", "object_image_type": "", "optimization":
-      null, "optimization_method": "", "order_of_acquisition": null, "order_of_preprocessing_operations":
-      "", "orthogonalization_description": "", "owner": 4432, "owner_name": "doellk",
-      "paper_url": "https://linkinghub.elsevier.com/retrieve/pii/S2213158219304735",
-      "parallel_imaging": "", "private": false, "proportion_male_subjects": null,
-      "pulse_sequence": "", "quality_control": "", "repetition_time": null, "resampled_voxel_size":
-      null, "scanner_make": "", "scanner_model": "", "skip_distance": null, "slice_thickness":
-      null, "slice_timing_correction_software": "", "smoothing_fwhm": null, "smoothing_type":
-      "", "software_package": "", "software_version": "", "subject_age_max": null,
-      "subject_age_mean": null, "subject_age_min": null, "target_resolution": null,
-      "target_template_image": "", "transform_similarity_metric": "", "type_of_design":
-      null, "url": "http://neurovault.org/collections/6034/", "used_b0_unwarping":
-      null, "used_dispersion_derivatives": null, "used_high_pass_filter": null, "used_intersubject_registration":
-      null, "used_motion_correction": null, "used_motion_regressors": null, "used_motion_susceptibiity_correction":
-      null, "used_orthogonalization": null, "used_reaction_time_regressor": null,
-      "used_slice_timing_correction": null, "used_smoothing": null, "used_temporal_derivatives":
-      null}, "name": "Atypical processing of social anticipation and feedback in borderline
-      personality disorder", "pmid": null, "publication": "NeuroImage: Clinical",
-      "source": "neurovault", "source_id": "6034", "source_updated_at": null, "updated_at":
-      "2023-06-21T22:17:27.973390+00:00", "user": null, "year": null}, {"analyses":
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-      "name": "37588", "points": [{"coordinates": [60.0, -64.0, 28.0], "id": "38c5vf66bcFo",
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-      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [15.0, -10.0,
-      -20.0], "id": "59D9X9dRgJ7T", "image": null, "kind": "unknown", "label_id":
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-      "5kFUkxRjSekg", "image": null, "kind": "unknown", "label_id": null, "space":
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-      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
-      []}, {"coordinates": [45.0, 14.0, -35.0], "id": "6iJiNa6Z5PLo", "image": null,
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-      "label_id": null, "space": "MNI", "values": []}, {"coordinates": [-51.0, 26.0,
-      -8.0], "id": "7KVqpZTFtAoh", "image": null, "kind": "unknown", "label_id": null,
-      "space": "MNI", "values": []}, {"coordinates": [-3.0, -49.0, 28.0], "id": "7bF2mDaoR8su",
-      "image": null, "kind": "unknown", "label_id": null, "space": "MNI", "values":
-      []}, {"coordinates": [18.0, -13.0, -17.0], "id": "Wme5NpZ4TDB9", "image": null,
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-      "label_id": null, "space": "MNI", "values": []}], "user": null, "weights": []}],
-      "authors": "Oetken S, Pauly KD, Gur RC, Schneider F, Habel U, Pohl A", "created_at":
-      "2023-05-19T23:38:25.513965+00:00", "description": null, "doi": "10.1016/j.neuropsychologia.2017.04.010",
-      "id": "4rDGfjjGNAgq", "metadata": null, "name": "Don''t worry, be happy - Neural
-      correlates of the influence of musically induced mood on self-evaluation.",
-      "pmid": "28392302", "publication": "Neuropsychologia", "source": "neurosynth",
-      "source_id": "28392302", "source_updated_at": null, "updated_at": "2023-06-21T22:17:27.973390+00:00",
-      "user": null, "year": 2017}, {"analyses": [{"conditions": [], "description":
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-      "Kong F, Hu S, Wang X, Song Y, Liu J", "created_at": "2023-05-19T23:38:25.513965+00:00",
-      "description": null, "doi": "10.1016/j.neuroimage.2014.11.033", "id": "uPDUNVQUJvpt",
-      "metadata": null, "name": "Neural correlates of the happy life: The amplitude
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-      "metadata": null, "name": "Mood-dependent integration in discourse comprehension:
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diff --git a/pynsc/tests/cassettes/test_run/test_run_workflow.yaml b/pynsc/tests/cassettes/test_run/test_run_workflow.yaml
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diff --git a/pynsc/tests/test_run.py b/pynsc/tests/test_run.py
deleted file mode 100644
index d4998b7..0000000
--- a/pynsc/tests/test_run.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import pytest
-from pynsc.run import Runner
-
-
-@pytest.mark.vcr(record_mode="once")
-def test_download_bundle():
-    runner = Runner(
-        meta_analysis_id="3opENJpHxRsH",
-        environment="staging",
-    )
-    runner.download_bundle()
-    assert runner.cached_studyset is not None
-    assert runner.cached_annotation is not None
-    assert runner.cached_specification is not None
-
-
-@pytest.mark.vcr(record_mode="once")
-def test_run_workflow():
-    runner = Runner(
-        meta_analysis_id="3opENJpHxRsH",
-        environment="staging",
-    )
-    runner.run_workflow()
-
-
-@pytest.mark.vcr(record_mode="once")
-def test_run_database_workflow():
-    runner = Runner(
-        meta_analysis_id="dRFtnAo9bhp3",
-        environment="staging",
-    )
-    runner.run_workflow()
-
-
-@pytest.mark.vcr(record_mode="once")
-def test_run_group_comparison_workflow():
-    runner = Runner(
-        meta_analysis_id="4CGQSSyaoWN3",
-        environment="staging",
-    )
-    runner.run_workflow()
-
-
-@pytest.mark.vcr(record_mode="once")
-def test_run_string_group_comparison_workflow():
-    runner = Runner(
-        meta_analysis_id="7joU2Siajs5X",
-        environment="staging",
-    )
-    runner.run_workflow()
-
-# def test_yifan_workflow():
-#     runner = Runner(
-#         meta_analysis_id="4WELjap2yCJm",
-#     )
-#     runner.run_workflow()