task config file good for now

Author: seohyonkim

_viash.yaml

@@ -1,34 +1,28 @@
 viash_version: 0.9.4
 
-# Step 1: Change the name of the task.
-# example: task_name_of_this_task
-name: task_template
+name: task_spatial_trajectory_inference
 organization: openproblems-bio
 version: dev
 
 license: MIT
-# Step 2: Add keywords to describe the task.
-keywords: [single-cell, openproblems, benchmark]
-# Step 3: Update the `task_template` to the name of the task from step 1.
+keywords: [single-cell, openproblems, benchmark, spatial, trajectory inference]
 links:
-  issue_tracker: https://github.com/openproblems-bio/task_template/issues
-  repository: https://github.com/openproblems-bio/task_template
+  issue_tracker: https://github.com/openproblems-bio/task_spatial_trajectory_inference/issues
+  repository: https://github.com/openproblems-bio/task_spatial_trajectory_inference
   docker_registry: ghcr.io
 
 
-# Step 4: Update the label, summary and description.
-# A unique, human-readable, short label. Used for creating summary tables and visualisations.
-label: Template
-summary: A one sentence summary of purpose and methodology. Used for creating an overview tables.
-description: |
-  Provide a clear and concise description of your task, detailing the specific problem it aims
-  to solve. Outline the input data types, the expected output, and any assumptions or constraints.
-  Be sure to explain any terminology or concepts that are essential for understanding the task.
+label: Spatial Trajectory Inference
+summary: Predicting the spatial trajectory of cells in a tissue based on spatial transcriptomics data.
+description: 
 
-  Explain the motivation behind your proposed task. Describe the biological or computational 
-  problem you aim to address and why it's important. Discuss the current state of research in
-  this area and any gaps or challenges that your task could help address. This section 
-  should convince readers of the significance and relevance of your task.
+  Spatial transcriptomics preserves each cell's physical position alongside its expression profile, enabling pseudotime prediction using 2D spatial context.
+  Different methods make different assumptions about resolution, input format, and output, and are further complicated by spatial batch effects not present in dissociated single-cell data.
+  While dynbenchmark resolved this comparison problem for non-spatial trajectory inference methods, no equivalent standardized benchmark exists for spatial pseudotime prediction, and existing method papers are validated only against each other or qualitative marker trends rather than tissues with independently known trajectories.
+
+  This task benchmarks pseudotime prediction methods on 2D tissue datasets with well-characterized ground-truth spatial axes.
+  Input data consists of AnnData objects containing 2D spatial transcriptomics data with spatial coordinates.
+  The output is a set of quantitative metric scores comparing each method's predicted pseudotime against ground truth, capturing both trajectory accuracy and preservation of relevant biological information.
 
 # A list of references to relevant literature. Each reference should be a DOI or a bibtex entry
 references:
@@ -47,32 +41,51 @@ references:
 
 info:
   image: The name of the image file to use for the component on the website.
-  # Step 5: Replace the task_template to the name of the task.
   test_resources:
     - type: s3
       path: s3://openproblems-data/resources_test/common/
       dest: resources_test/common
     - type: s3
-      path: s3://openproblems-data/resources_test/task_template/
-      dest: resources_test/task_template
+      path: s3://openproblems-data/resources_test/task_spatial_trajectory_inference/
+      dest: resources_test/task_spatial_trajectory_inference
 
-# Step 6: Update the authors of the task.
 authors: 
-  # Full name of the author, usually in the name of FirstName MiddleName LastName.
-  - name: John Doe
-    # Role of the author. Possible values:
-    # 
-    # * `"author"`: Authors who have made substantial contributions to the component.
-    # * `"maintainer"`: The maintainer of the component.
-    # * `"contributor"`: Authors who have made smaller contributions (such as code patches etc.).
+  - name: Chit Tong Lio
+    roles: [ "author", "maintainer" ]
+    info: 
+      github: yollct
+      orcid: 0000-0003-2297-831X
+      email: chit-tong.lio@tum.de
+  - name: Seo Hyon Kim
+    roles: [ "author", "maintainer" ]
+    info: 
+      github: seohyonkim
+      orcid: 0009-0007-3062-4681
+      email: seohyon.l.kim@gmail.com
+  - name: Wenjia Zhong
+    roles: [ "author", "maintainer" ]
+    info: 
+      github: Wenjia218
+      orcid: 0009-0009-1594-8009
+      email: wenjia.zhong@tum.de
+  - name: Luisa Katharina Bender
+    roles: [ "author", "maintainer" ]
+    info: 
+      github: luisabender
+      orcid: 0009-0001-8753-7307
+      email: luisa.bender@tum.de
+  - name: Florian Röckl
+    roles: [ "author", "maintainer" ]
+    info: 
+      github: floro5
+      orcid: 0009-0009-6050-890X
+      email: florian.roeckl@tum.de
+  - name: Jonathan Unger
     roles: [ "author", "maintainer" ]
-    # Additional information on the author
     info: 
-      github: johndoe
-      orcid: 0000-0000-0000-0000
-      email: john@doe.me
-      twitter: johndoe
-      linkedin: johndoe
+      github: Jonique02
+      orcid: 0009-0009-5022-2975
+      email: jonathan.unger@tum.de
 
 # Step 7: Remove all of the comments of the steps you completed