diff --git a/cirro/sdk/process.py b/cirro/sdk/process.py
index 9777fd1..282924f 100644
--- a/cirro/sdk/process.py
+++ b/cirro/sdk/process.py
@@ -1,10 +1,12 @@
 from typing import List, Union
 
-from cirro_api_client.v1.models import Process, Executor, ProcessDetail, CustomPipelineSettings, PipelineCode
+from cirro_api_client.v1.models import Process, Executor, ProcessDetail, CustomPipelineSettings, PipelineCode, \
+    RunAnalysisRequest, RunAnalysisRequestParams
 
 from cirro.cirro_client import CirroApi
 from cirro.models.form_specification import ParameterSpecification
 from cirro.sdk.asset import DataPortalAssets, DataPortalAsset
+from cirro.sdk.exceptions import DataPortalInputError
 
 
 class DataPortalProcess(DataPortalAsset):
@@ -95,6 +97,82 @@ def get_parameter_spec(self) -> ParameterSpecification:
         """
         return self._client.processes.get_parameter_spec(self.id)
 
+    def run_analysis(
+            self,
+            name: str = None,
+            project_id: str = None,
+            datasets: list = None,
+            description: str = "",
+            params=None,
+            notifications_emails: List[str] = None,
+            compute_environment: str = None,
+            resume_dataset_id: str = None
+    ) -> str:
+        """
+        Runs this process on one or more input datasets, returns the ID of the newly created dataset.
+
+        Args:
+            name (str): Name of newly created dataset
+            project_id (str): ID of the project to run the analysis in
+            datasets (List[DataPortalDataset or str]): One or more input datasets
+             (as DataPortalDataset objects or dataset ID strings)
+            description (str): Description of newly created dataset
+            params (dict): Analysis parameters
+            notifications_emails (List[str]): Notification email address(es)
+            compute_environment (str): Name or ID of compute environment to use,
+             if blank it will run in AWS
+            resume_dataset_id (str): ID of dataset to resume from, used for caching task execution.
+             It will attempt to re-use the previous output to minimize duplicate work.
+            Note that Nextflow does not require this parameter, as it will automatically resume
+             from any previous attempts using a global cache.
+
+        Returns:
+            dataset_id (str): ID of newly created dataset
+        """
+        if name is None:
+            raise DataPortalInputError("Must specify 'name' for run_analysis")
+        if project_id is None:
+            raise DataPortalInputError("Must specify 'project_id' for run_analysis")
+        if not datasets:
+            raise DataPortalInputError("Must specify 'datasets' for run_analysis")
+        if notifications_emails is None:
+            notifications_emails = []
+        if params is None:
+            params = {}
+
+        # Accept DataPortalDataset objects or raw ID strings
+        source_dataset_ids = [
+            ds if isinstance(ds, str) else ds.id
+            for ds in datasets
+        ]
+
+        if compute_environment:
+            compute_environments = self._client.compute_environments.list_environments_for_project(
+                project_id=project_id
+            )
+            compute_environment = next(
+                (env for env in compute_environments
+                 if env.name == compute_environment or env.id == compute_environment),
+                None
+            )
+            if compute_environment is None:
+                raise DataPortalInputError(f"Compute environment '{compute_environment}' not found")
+
+        resp = self._client.execution.run_analysis(
+            project_id=project_id,
+            request=RunAnalysisRequest(
+                name=name,
+                description=description,
+                process_id=self.id,
+                source_dataset_ids=source_dataset_ids,
+                params=RunAnalysisRequestParams.from_dict(params),
+                notification_emails=notifications_emails,
+                resume_dataset_id=resume_dataset_id,
+                compute_environment_id=compute_environment.id if compute_environment else None
+            )
+        )
+        return resp.id
+
 
 class DataPortalProcesses(DataPortalAssets[DataPortalProcess]):
     """Collection of DataPortalProcess objects."""