diff --git a/Dockerfile b/Dockerfile
index 8253cef..92a16b0 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -27,12 +27,19 @@ COPY app/ ./app/
 # Copy built frontend from GitHub Actions build
 COPY ui/dist ./ui/dist
 
-# Expose port
-EXPOSE 8000
+# Create startup script that properly handles runtime PORT variable
+RUN echo '#!/bin/sh\n\
+PORT="${PORT:-8080}"\n\
+echo "Starting server on port $PORT"\n\
+exec /app/.venv/bin/uvicorn app.main:app --host 0.0.0.0 --port "$PORT"' > /app/start.sh && \
+  chmod +x /app/start.sh
+
+# Expose port 8080 (Cloud Run default)
+EXPOSE 8080
 
 # Health check
 HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
-  CMD curl -f http://localhost:8000/ || exit 1
+  CMD curl -f http://localhost:${PORT:-8080}/ || exit 1
 
 # Run the application
-CMD ["/app/.venv/bin/uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["/app/start.sh"]
diff --git a/app/config.py b/app/config.py
index 583ab31..3fd8866 100644
--- a/app/config.py
+++ b/app/config.py
@@ -12,18 +12,29 @@ class DevelopmentConfig(BaseConfig):
     CORS_ORIGINS = [
         "http://localhost:3000",
         "http://localhost:5173",  # Vite dev server
+        "http://localhost:5174",  # Vite dev server
         "http://127.0.0.1:5173",  # Vite dev server alternative
+        "http://127.0.0.1:5174",  # Vite dev server alternative
         "http://localhost:4173",  # Vite preview server
         "http://127.0.0.1:4173",  # Vite preview server alternative
+        "http://localhost:8080",  # Docker local
+        "http://localhost:8000",  # Alternative local
     ]
 
 
 class ProductionConfig(BaseConfig):
     DEBUG = False
-    CORS_ORIGINS = [""]
+    # For Cloud Run, you need to add your actual domain
+    CORS_ORIGINS = (
+        os.getenv("CORS_ORIGINS", "").split(",") if os.getenv("CORS_ORIGINS") else ["*"]
+    )
 
 
 def get_config():
+    # Check for DEBUG env var first, then APP_ENV
+    if os.getenv("DEBUG", "").lower() == "true":
+        return DevelopmentConfig
+
     env = os.getenv("APP_ENV", "development")
     if env == "production":
         return ProductionConfig
diff --git a/app/controllers/hello.py b/app/controllers/hello.py
deleted file mode 100644
index e69de29..0000000
diff --git a/app/main.py b/app/main.py
index a9751f6..62fb1a8 100644
--- a/app/main.py
+++ b/app/main.py
@@ -6,8 +6,6 @@
 from starlette.exceptions import HTTPException as StarletteHTTPException
 from starlette.responses import JSONResponse
 from app.config import get_config
-from app.routers.pathways import router as pathways_router
-from app.routers.umap_router import router 
 from app.routers import gsea
 from app.scripts.prepare_gene_lists import generate_all_library_gene_lists
 
@@ -45,8 +43,6 @@
 
 # Include routers
 app.include_router(gsea.router, prefix="/api", tags=["GSEA"])
-app.include_router(pathways_router)
-app.include_router(router, prefix="/umap")
 
 
 # Mount static files for the React app
diff --git a/app/models/__init__.py b/app/models/__init__.py
index e69de29..4df7914 100644
--- a/app/models/__init__.py
+++ b/app/models/__init__.py
@@ -0,0 +1,3 @@
+from app.models.gsea import Gene, GseaJsonRequest
+
+__all__ = ["Gene", "GseaJsonRequest"]
diff --git a/app/models/gsea.py b/app/models/gsea.py
new file mode 100644
index 0000000..e8ec94c
--- /dev/null
+++ b/app/models/gsea.py
@@ -0,0 +1,24 @@
+from pydantic import BaseModel, Field, field_validator
+from typing import List
+
+
+class Gene(BaseModel):
+    """Individual gene with symbol and score."""
+
+    symbol: str = Field(..., description="Gene symbol (e.g., 'BRCA1', 'TP53')")
+    globalScore: float = Field(..., description="Gene score for ranking")
+
+
+class GseaJsonRequest(BaseModel):
+    """Request model for JSON-based GSEA endpoint."""
+
+    genes: List[Gene] = Field(
+        ..., min_length=1, description="List of genes with symbols and scores"
+    )
+
+    @field_validator("genes")
+    @classmethod
+    def validate_genes_not_empty(cls, v):
+        if not v or len(v) == 0:
+            raise ValueError("Genes list cannot be empty")
+        return v
diff --git a/app/routers/__init__.py b/app/routers/__init__.py
index e69de29..3c10ace 100644
--- a/app/routers/__init__.py
+++ b/app/routers/__init__.py
@@ -0,0 +1,5 @@
+"""API routers for the Pathways API."""
+
+from app.routers import gsea
+
+__all__ = ["gsea"]
diff --git a/app/routers/gsea.py b/app/routers/gsea.py
index 8c73437..611ae4e 100644
--- a/app/routers/gsea.py
+++ b/app/routers/gsea.py
@@ -1,6 +1,8 @@
 from fastapi import APIRouter, UploadFile, File, Query, HTTPException
 from typing import Literal
-from app.services.gsea import run_gsea, available_gmt_files
+from app.services.gsea import run_gsea_from_dataframe, available_gmt_files
+from app.models.gsea import GseaJsonRequest
+from app.utils.gsea_utils import validate_gsea_dataframe, handle_gsea_error
 import tempfile
 import pandas as pd
 import os
@@ -8,46 +10,119 @@
 
 router = APIRouter()
 
+
 @router.get("/gsea/libraries")
 async def list_gmt_files():
     """List available GMT libraries."""
     return list(available_gmt_files().keys())
 
 
-@router.post("/gsea")
-async def gsea_endpoint(
-    tsv_file: UploadFile = File(..., description="TSV file containing at least 2 columns: 'symbol' and 'globalScore'"),
+@router.post("/gsea/analyze/file")
+async def analyze_gsea_from_file(
+    tsv_file: UploadFile = File(
+        ...,
+        description="TSV file containing at least 2 columns: 'symbol' and 'globalScore'",
+    ),
     gmt_name: str = Query(..., description="GMT library name (without .gmt extension)"),
     analysis_direction: Literal["one_sided_positive", "one_sided_negative", "two_sided"] = Query(
         default="one_sided_positive",
         description="Analysis direction: 'one_sided_positive' filters NES > 0, 'one_sided_negative' filters NES < 0, 'two_sided' returns all results"
-    )
+    ),
 ):
+    """
+    Run GSEA analysis from uploaded TSV file.
+
+    Upload a TSV file with gene symbols and scores to perform Gene Set Enrichment Analysis.
+
+    Example:
+        POST /api/gsea/analyze/file?gmt_name=Reactome/ReactomePathways_2025
+        Content-Type: multipart/form-data
+        Body: file=your_data.tsv
+    """
     # Validate file extension
     if not tsv_file.filename.endswith(".tsv"):
         raise HTTPException(status_code=400, detail="File must be .tsv format")
 
-    # Save to temp file
+    # Read and validate file
     with tempfile.NamedTemporaryFile(delete=False, suffix=".tsv") as tmp:
         content = await tsv_file.read()
         tmp.write(content)
         tsv_path = tmp.name
 
-    # Validate TSV structure
     try:
-        df = pd.read_csv(tsv_path, sep="\t", nrows=1)  # read first row
-        if not {"symbol", "globalScore"}.issubset(df.columns) and not {0, 1}.issubset(df.columns):
-            raise ValueError("TSV must contain 'symbol' and 'globalScore' columns (or two unnamed columns).")
-    except Exception as e:
-        os.unlink(tsv_path)
-        raise HTTPException(status_code=400, detail=f"Invalid TSV format: {str(e)}")
+        # Load and validate DataFrame
+        df = pd.read_csv(tsv_path, sep="\t")
+        df = validate_gsea_dataframe(df)
 
-    # Run GSEA
-    try:
-        res_df, missing_stats = run_gsea(input_tsv=tsv_path, gmt_name=gmt_name)
+        # Run GSEA
+        res_df, input_overlap = run_gsea_from_dataframe(df, gmt_name)
+
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise handle_gsea_error(e)
     finally:
         # Clean up temp file
-        os.unlink(tsv_path)
+        if os.path.exists(tsv_path):
+            os.unlink(tsv_path)
+
+    # Filter by NES based on analysis direction
+    if analysis_direction == "one_sided_positive":
+        res_df = res_df[res_df["NES"] > 0].copy()
+    elif analysis_direction == "one_sided_negative":
+        res_df = res_df[res_df["NES"] < 0].copy()
+
+    # Replace NaN/Inf with JSON-safe values
+    res_df = res_df.replace([np.inf, -np.inf], None)
+    res_df = res_df.where(pd.notna(res_df), None)
+
+    return {
+        "results": res_df.to_dict(orient="records"),
+        "input_overlap": input_overlap,
+    }
+
+
+@router.post("/gsea/analyze/json")
+async def analyze_gsea_from_json(
+    request: GseaJsonRequest,
+    gmt_name: str = Query(..., description="GMT library name (without .gmt extension)"),
+    analysis_direction: Literal["one_sided_positive", "one_sided_negative", "two_sided"] = Query(
+        default="one_sided_positive",
+        description="Analysis direction: 'one_sided_positive' filters NES > 0, 'one_sided_negative' filters NES < 0, 'two_sided' returns all results"
+    ),
+):
+    """
+    Run GSEA analysis from JSON payload.
+
+    Send gene data as JSON to perform Gene Set Enrichment Analysis.
+
+    Example:
+        POST /api/gsea/analyze/json?gmt_name=Reactome/ReactomePathways_2025
+        Content-Type: application/json
+        Body: {
+            "genes": [
+                {"symbol": "BRCA1", "globalScore": 0.95},
+                {"symbol": "TP53", "globalScore": 0.87}
+            ]
+        }
+    """
+    try:
+        # Convert request to DataFrame
+        genes_data = [
+            {"symbol": g.symbol, "globalScore": g.globalScore} for g in request.genes
+        ]
+        df = pd.DataFrame(genes_data)
+
+        # Validate DataFrame (should already be valid via Pydantic, but double-check)
+        df = validate_gsea_dataframe(df)
+
+        # Run GSEA directly (no file I/O needed!)
+        res_df, input_overlap = run_gsea_from_dataframe(df, gmt_name)
+
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise handle_gsea_error(e)
 
     # Filter by NES based on analysis direction
     if analysis_direction == "one_sided_positive":
@@ -61,5 +136,5 @@ async def gsea_endpoint(
 
     return {
         "results": res_df.to_dict(orient="records"),
-        "input_overlap": missing_stats,
+        "input_overlap": input_overlap,
     }
diff --git a/app/routers/pathways.py b/app/routers/pathways.py
deleted file mode 100644
index f9d241c..0000000
--- a/app/routers/pathways.py
+++ /dev/null
@@ -1,53 +0,0 @@
-from typing import Any
-from fastapi import APIRouter, HTTPException, UploadFile, File, Form
-from pathlib import Path
-
-from app.services.gsea import available_gmt_files, run_gsea
-
-router = APIRouter(prefix="/pathways", tags=["pathways"])
-
-
-@router.get("/available", response_model=list[str])
-async def list_libraries():
-    """
-    Return available GMT libraries under data/gmt (subfolders).
-    Example: ["Reactome/reactome2022", "GO/go2022"]
-    """
-    try:
-        return list(available_gmt_files().keys())
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-@router.post("/gsea", response_model=list[dict[str, Any]])
-async def run_gsea_endpoint(
-    gmt_name: str = Form(..., description="Library name, e.g. Reactome/reactome2022"),
-    processes: int = Form(4, description="Number of CPU processes"),
-    file: UploadFile = File(..., description="TSV file with 'symbol' and 'globalScore'")
-):
-    """
-    Run GSEA on an uploaded input file using a chosen GMT library.
-    """
-    tmp_path = Path(f"/tmp/{file.filename}")
-    try:
-        # Save uploaded file to a temporary path
-        with tmp_path.open("wb") as f:
-            f.write(await file.read())
-
-        res_df, _missing_stats = run_gsea(
-            input_tsv=tmp_path,
-            gmt_name=gmt_name,
-            processes=processes,
-        )
-
-        # Return as JSON records
-        return res_df.to_dict(orient="records")
-
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-    finally:
-        # Clean up temp file
-        if tmp_path.exists():
-            tmp_path.unlink()
diff --git a/app/routers/umap_router.py b/app/routers/umap_router.py
deleted file mode 100644
index 160998a..0000000
--- a/app/routers/umap_router.py
+++ /dev/null
@@ -1,71 +0,0 @@
-import os
-import pandas as pd
-from fastapi import APIRouter, Query, HTTPException
-from fastapi.responses import HTMLResponse
-from app.services.umap_service import perform_umap_clustering_api
-
-router = APIRouter()
-
-@router.get("/run", response_class=HTMLResponse)
-def run_umap(
-    disease_id: str = Query(..., description="The disease ID (e.g., 'EFO_0000094')"),
-    library: str = Query(..., description="The library name (e.g., 'open_targets')"),
-    n_neighbors: int = Query(10),
-    min_dist: float = Query(0.5),
-    min_cluster_size: int = Query(12),
-    umap_dimensions: int = Query(2)
-):
-    try:
-        # Run UMAP & clustering
-        output_file = perform_umap_clustering_api(
-            disease_id=disease_id,
-            library=library,
-            n_neighbors=n_neighbors,
-            min_dist=min_dist,
-            min_cluster_size=min_cluster_size,
-            umap_dimensions=umap_dimensions
-        )
-
-        # Read TSV into a DataFrame
-        df = pd.read_csv(output_file, sep='\t')
-
-        # Convert to HTML table (with some basic styling)
-        html = df.to_html(index=False, classes="table table-bordered table-striped")
-
-        # Wrap in a basic HTML template
-        html_template = f"""
-        <html>
-            <head>
-                <title>UMAP Clustering Results</title>
-                <style>
-                    body {{
-                        font-family: Arial, sans-serif;
-                        margin: 40px;
-                    }}
-                    .table {{
-                        border-collapse: collapse;
-                        width: 100%;
-                    }}
-                    .table th, .table td {{
-                        border: 1px solid #ddd;
-                        padding: 8px;
-                    }}
-                    .table th {{
-                        background-color: #f2f2f2;
-                        text-align: left;
-                    }}
-                    .table-striped tr:nth-child(even) {{
-                        background-color: #f9f9f9;
-                    }}
-                </style>
-            </head>
-            <body>
-                <h2>UMAP Clustering Results for <code>{disease_id}</code></h2>
-                {html}
-            </body>
-        </html>
-        """
-        return HTMLResponse(content=html_template)
-
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
diff --git a/app/services/__init__.py b/app/services/__init__.py
index e69de29..943a13f 100644
--- a/app/services/__init__.py
+++ b/app/services/__init__.py
@@ -0,0 +1,15 @@
+"""Service layer for the Pathways API."""
+
+from app.services.gsea import (
+    available_gmt_files,
+    run_gsea,
+    run_gsea_from_dataframe,
+    load_custom_gmt,
+)
+
+__all__ = [
+    "available_gmt_files",
+    "run_gsea",
+    "run_gsea_from_dataframe",
+    "load_custom_gmt",
+]
diff --git a/app/services/gsea.py b/app/services/gsea.py
index 9ba2c9e..66e51b4 100644
--- a/app/services/gsea.py
+++ b/app/services/gsea.py
@@ -16,20 +16,21 @@ def get_approved_symbols_from_gcs():
     """
     # Initialize GCS filesystem
     fs = gcsfs.GCSFileSystem()
-    
+
     # Define the GCS path to the target directory
     gcs_path = "open-targets-pre-data-releases/25.09/output/target/"
-    
+
     # Read all parquet files in the directory as a single dataset
     # This is much more efficient than downloading individual files
     df = pd.read_parquet(gcs_path, filesystem=fs, columns=["approvedSymbol"])
-    
+
     # Extract unique approved symbols (excluding NaN values)
     approved_symbols = set(df["approvedSymbol"].dropna().astype(str))
 
-    
+
     return approved_symbols
 
+
 def load_custom_gmt(path):
     p = Path(path)
     with p.open("r") as f:
@@ -39,6 +40,7 @@ def load_custom_gmt(path):
             if (parts := line.strip().split("\t")) and len(parts) > MIN_GENE_COL_IDX
         }
 
+
 def available_gmt_files():
     """
     Return available GMT libraries as:
@@ -62,14 +64,24 @@ def available_gmt_files():
             }
     return libraries
 
-def run_gsea(input_tsv=None, gmt_name=None, processes=4):
-    """
-    Run GSEA using a chosen GMT library and its hierarchy (if present).
-    Pathway size is computed from the GMT (total genes in the pathway).
-    Ensure 'Number of input genes' and 'Pathway size' are integers (no .0).
+
+def run_gsea_from_dataframe(
+    df: pd.DataFrame, gmt_name: str, processes: int = 4
+) -> tuple[pd.DataFrame, dict]:
     """
-    input_tsv = Path(input_tsv)
+    Run GSEA using a DataFrame directly (no file required).
+
+    Args:
+        df: DataFrame with 'symbol' and 'globalScore' columns, already validated
+        gmt_name: Name of GMT library to use
+        processes: Number of CPU processes
 
+    Returns:
+        Tuple of (DataFrame with GSEA results, overlap_stats dict)
+
+    Raises:
+        ValueError: If gmt_name is invalid or DataFrame is missing required columns
+    """
     gmt_files = available_gmt_files()
     if not gmt_name or gmt_name not in gmt_files:
         msg = "Invalid gmt_name. Choose from: " + str(list(gmt_files.keys()))
@@ -107,16 +119,9 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4):
                     # if no braces, map Term itself as ID
                     id_to_genes[term] = genes
 
-    # --- Load input file safely ---
-    df = pd.read_csv(input_tsv, sep="\t")
-
-    # Allow unnamed columns (0,1) and rename to expected headers
-    if set(df.columns) == set(range(len(df.columns))):
-        df = df.rename(columns={0: "symbol", 1: "globalScore"})
-
+    # Ensure DataFrame is properly formatted
     if not {"symbol", "globalScore"}.issubset(df.columns):
-        msg = "Input file must contain 'symbol' and 'globalScore' columns."
-        raise ValueError(msg)
+        raise ValueError("DataFrame must contain 'symbol' and 'globalScore' columns.")
 
     # Keep only required columns
     df = df[["symbol", "globalScore"]].copy()
@@ -170,7 +175,9 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4):
     if contains_braces:
         term_series = res_df["Term"]
         res_df["ID"] = term_series.str.extract(r"\{([^}]+)\}", expand=False).fillna("")
-        res_df["Term"] = term_series.str.replace(r"\s*\{[^}]+\}", "", regex=True).str.strip()
+        res_df["Term"] = term_series.str.replace(
+            r"\s*\{[^}]+\}", "", regex=True
+        ).str.strip()
     else:
         res_df["ID"] = res_df["Term"]  # use Term as ID directly
 
@@ -261,3 +268,33 @@ def safe_int_col(df_, col_name):
 
     return res_df, overlap_stats
 
+
+def run_gsea(input_tsv=None, gmt_name=None, processes=4):
+    """
+    Run GSEA from a TSV file path (backward compatible).
+
+    Args:
+        input_tsv: Path to TSV file with 'symbol' and 'globalScore' columns
+        gmt_name: Name of GMT library to use
+        processes: Number of CPU processes
+
+    Returns:
+        Tuple of (DataFrame with GSEA results, overlap_stats dict)
+
+    Raises:
+        ValueError: If gmt_name is invalid or file is missing required columns
+    """
+    if not input_tsv:
+        raise ValueError("input_tsv parameter is required")
+
+    input_tsv = Path(input_tsv)
+
+    # Load input file
+    df = pd.read_csv(input_tsv, sep="\t")
+
+    # Handle unnamed columns (legacy support)
+    if set(df.columns) == set(range(len(df.columns))):
+        df = df.rename(columns={0: "symbol", 1: "globalScore"})
+
+    # Validate and run GSEA using the DataFrame-based function
+    return run_gsea_from_dataframe(df, gmt_name, processes)
diff --git a/app/services/pathways_service.py b/app/services/pathways_service.py
deleted file mode 100644
index dcc025e..0000000
--- a/app/services/pathways_service.py
+++ /dev/null
@@ -1,41 +0,0 @@
-from typing import Any, List, Optional
-
-from pyspark.sql import DataFrame, Row
-from pyspark.sql.functions import col
-
-from app.utils.spark import get_spark_session
-
-BASE_PATH = "data/table_view"
-
-def fetch_pathways(
-    disease_id: str,
-    library: str,
-    fdr_lt: Optional[float] = None,
-    hide_leading_edge: bool = False,
-) -> List[dict[str, Any]]:
-    """
-    Load the parquet partition for `library`/`disease_id`,
-    apply optional filters, drop `diseaseId` and optional columns,
-    and return as list of dicts.
-    """
-    spark = get_spark_session()
-    path = f"{BASE_PATH}/{library}/diseaseId={disease_id}"
-    
-    # Read the partition
-    df: DataFrame = spark.read.parquet(path)
-    
-    # --- ALWAYS DROP the partition column so it doesn't appear in output ---
-    if "diseaseId" in df.columns:
-        df = df.drop("diseaseId")
-    
-    # Optional filtering
-    if fdr_lt is not None:
-        df = df.filter(col("FDR") < fdr_lt)
-    
-    # Optional column drop
-    if hide_leading_edge and "Leading edge genes" in df.columns:
-        df = df.drop("Leading edge genes")
-    
-    # Collect and convert each Row to a native dict
-    rows: list[Row] = df.collect()
-    return [row.asDict(recursive=True) for row in rows]
diff --git a/app/services/umap_service.py b/app/services/umap_service.py
deleted file mode 100644
index 0256b64..0000000
--- a/app/services/umap_service.py
+++ /dev/null
@@ -1,102 +0,0 @@
-import os
-import pandas as pd
-import numpy as np
-import umap
-import hdbscan
-from scipy.spatial.distance import pdist, squareform
-from fastapi.responses import FileResponse  # optional
-
-
-def poincare_dist(u, v):
-    norm_u = np.linalg.norm(u)
-    norm_v = np.linalg.norm(v)
-    norm_diff = np.linalg.norm(u - v)
-    denom = (1 - norm_u ** 2) * (1 - norm_v ** 2)
-    if denom <= 0:
-        return float('inf')
-    argument = 1 + 2 * (norm_diff ** 2) / denom
-    argument = max(argument, 1.0)
-    return np.arccosh(argument)
-
-
-def compute_poincare_distance_matrix(embedding_matrix):
-    return squareform(pdist(embedding_matrix, metric=poincare_dist))
-
-
-def perform_umap_clustering_api(
-    disease_id: str,
-    library: str,
-    n_neighbors: int = 10,
-    min_dist: float = 0.5,
-    min_cluster_size: int = 12,
-    umap_dimensions: int = 2,
-    base_data_dir: str = "data/umap_dynamic"
-) -> str:
-    """
-    Perform UMAP and HDBSCAN clustering on embeddings andmetadata for a given disease_id and library.
-    Returns path to the resulting TSV file.
-    """
-
-    # Ensure folder uses 'diseaseId=' prefix
-    folder_name = disease_id
-    if not disease_id.startswith("diseaseId="):
-        folder_name = f"diseaseId={disease_id}"
-
-    # Updated paths include the library directory
-    coordinates_parquet_dir = os.path.join(base_data_dir, "target_embeddings", library, folder_name)
-    metadata_parquet_dir = os.path.join(base_data_dir, "target_metadata", library, folder_name)
-    output_dir = os.path.join(base_data_dir, "output", library, folder_name)
-
-    # Load parquet datasets from directories
-    metadata = pd.read_parquet(metadata_parquet_dir).query("geneticScore.notnull()")
-    coords_df = pd.read_parquet(coordinates_parquet_dir)
-
-    # Prepare coordinates
-    coords_df = coords_df.rename(columns={coords_df.columns[0]: 'approvedSymbol'})
-    coord_columns = coords_df.columns[1:]
-    coords_df[coord_columns] = coords_df[coord_columns].astype(float)
-
-    # Merge embeddings with metadata
-    merged_df = pd.merge(metadata, coords_df, on='approvedSymbol', how='inner')
-
-    # Validate embedding norms (Poincaré ball condition)
-    embedding_matrix = merged_df[coord_columns].values
-    norms = np.linalg.norm(embedding_matrix, axis=1)
-    if np.any(norms >= 1):
-        raise ValueError("Some embeddings lie outside the Poincaré ball (norm >= 1).")
-
-    # Compute Poincaré distances
-    distance_matrix = compute_poincare_distance_matrix(embedding_matrix)
-
-    # UMAP dimensionality reduction
-    reducer = umap.UMAP(
-        n_neighbors=n_neighbors,
-        min_dist=min_dist,
-        n_components=umap_dimensions,
-        metric='precomputed',
-        random_state=42
-    )
-    embedding_umap = reducer.fit_transform(distance_matrix)
-
-    # HDBSCAN clustering
-    clusterer = hdbscan.HDBSCAN(
-        min_cluster_size=min_cluster_size,
-        min_samples=1,
-        metric='precomputed'
-    )
-    cluster_labels = clusterer.fit_predict(distance_matrix)
-
-    # Append UMAP and cluster labels
-    for dim in range(umap_dimensions):
-        merged_df[f'UMAP {dim+1}'] = embedding_umap[:, dim]
-    merged_df['cluster'] = cluster_labels
-
-    # Drop original embedding columns
-    output_df = merged_df.drop(columns=coord_columns)
-
-    # Save result to TSV
-    os.makedirs(output_dir, exist_ok=True)
-    output_file = os.path.join(output_dir, f"{disease_id}_clusters.tsv")
-    output_df.to_csv(output_file, sep='\t', index=False)
-
-    return output_file
\ No newline at end of file
diff --git a/app/utils/__init__.py b/app/utils/__init__.py
index e69de29..1245e14 100644
--- a/app/utils/__init__.py
+++ b/app/utils/__init__.py
@@ -0,0 +1,5 @@
+"""Utility functions for the Pathways API."""
+
+from app.utils.gsea_utils import validate_gsea_dataframe, handle_gsea_error
+
+__all__ = ["validate_gsea_dataframe", "handle_gsea_error"]
diff --git a/app/utils/gsea_utils.py b/app/utils/gsea_utils.py
new file mode 100644
index 0000000..0de35f4
--- /dev/null
+++ b/app/utils/gsea_utils.py
@@ -0,0 +1,67 @@
+from fastapi import HTTPException
+import pandas as pd
+
+
+def validate_gsea_dataframe(df: pd.DataFrame) -> pd.DataFrame:
+    """
+    Validate and normalize a DataFrame for GSEA analysis.
+
+    Args:
+        df: Input DataFrame to validate
+
+    Returns:
+        Normalized DataFrame with 'symbol' and 'globalScore' columns, sorted by score
+
+    Raises:
+        HTTPException: If validation fails
+    """
+    # Handle unnamed columns (legacy support)
+    if set(df.columns) == set(range(len(df.columns))):
+        df = df.rename(columns={0: "symbol", 1: "globalScore"})
+
+    # Validate required columns
+    if not {"symbol", "globalScore"}.issubset(df.columns):
+        raise HTTPException(
+            status_code=400,
+            detail="Input must contain 'symbol' and 'globalScore' columns",
+        )
+
+    # Extract only required columns and sort
+    df = df[["symbol", "globalScore"]].copy()
+    df = df.sort_values("globalScore", ascending=False)
+
+    return df
+
+
+def handle_gsea_error(error: Exception) -> HTTPException:
+    """
+    Convert GSEA analysis errors into user-friendly HTTP exceptions.
+
+    Args:
+        error: The exception that occurred during GSEA analysis
+
+    Returns:
+        HTTPException with appropriate status code and message
+    """
+    error_str = str(error).lower()
+
+    if isinstance(error, ValueError):
+        if any(keyword in error_str for keyword in ["nan", "solver cannot continue"]):
+            return HTTPException(
+                status_code=400,
+                detail=(
+                    "GSEA analysis failed. This usually means the gene symbols in your input "
+                    "don't match any pathways in the selected GMT library. Please verify that "
+                    "your input contains valid gene symbols (e.g., 'BRCA1', 'TP53', 'EGFR') "
+                    "rather than disease names or other identifiers."
+                ),
+            )
+        else:
+            return HTTPException(
+                status_code=400, detail=f"GSEA analysis error: {str(error)}"
+            )
+    else:
+        return HTTPException(
+            status_code=500,
+            detail=f"Unexpected error during GSEA analysis: {str(error)}",
+        )
diff --git a/app/utils/spark.py b/app/utils/spark.py
deleted file mode 100644
index 8f27533..0000000
--- a/app/utils/spark.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from pyspark.sql import SparkSession
-
-_spark = None
-
-def get_spark_session() -> SparkSession:
-    global _spark
-    if _spark is None:
-        _spark = (
-            SparkSession
-            .builder
-            .appName("PathwaysAPI")
-            .config("spark.ui.showConsoleProgress", "false")
-            .getOrCreate()
-        )
-    return _spark
diff --git a/app/utils/xml_parser.py b/app/utils/xml_parser.py
deleted file mode 100644
index a15b82e..0000000
--- a/app/utils/xml_parser.py
+++ /dev/null
@@ -1,11 +0,0 @@
-import xml.etree.ElementTree as ET
-
-
-def xml_to_plain_text(xml_string):
-    try:
-        root = ET.fromstring(xml_string)
-        plain_text = "".join(root.itertext())
-        return plain_text.strip()
-    except ET.ParseError as e:
-        print(f"Error al analizar el XML: {e}")
-        return None
diff --git a/dev.sh b/dev.sh
new file mode 100644
index 0000000..241c68c
--- /dev/null
+++ b/dev.sh
@@ -0,0 +1,57 @@
+#!/bin/bash
+
+# Local development script for pathways-api
+
+echo "🚀 Starting Pathways API local development environment..."
+
+# Function to cleanup on exit
+cleanup() {
+    echo "🛑 Stopping services..."
+    docker-compose down
+    exit
+}
+
+# Set trap to cleanup on script exit
+trap cleanup EXIT INT TERM
+
+# Check if running in Docker mode or local mode
+if [ "$1" = "docker" ]; then
+    echo "📦 Running in Docker mode..."
+    
+    # Build and run with docker-compose
+    docker-compose build
+    docker-compose up -d
+    
+    echo "✅ API running at http://localhost:8080"
+    echo "📝 Logs: docker-compose logs -f pathways-api"
+    
+    # Wait for services
+    docker-compose logs -f
+    
+elif [ "$1" = "local" ]; then
+    echo "💻 Running in local development mode..."
+    
+    # Start backend
+    echo "🔧 Starting backend..."
+    cd /Users/carlos_cruz/projects/ot/pathways-api
+    PORT=8080 uvicorn app.main:app --reload --host 0.0.0.0 --port 8080 &
+    BACKEND_PID=$!
+    
+    # Start frontend
+    echo "🎨 Starting frontend..."
+    cd ui
+    npm run dev &
+    FRONTEND_PID=$!
+    
+    echo "✅ Backend running at http://localhost:8080"
+    echo "✅ Frontend running at http://localhost:5173"
+    
+    # Wait for both processes
+    wait $BACKEND_PID $FRONTEND_PID
+    
+else
+    echo "Usage: $0 [docker|local]"
+    echo "  docker - Run everything in Docker"
+    echo "  local  - Run backend and frontend locally"
+    exit 1
+fi
diff --git a/docker-compose.yml b/docker-compose.yml
index f1ab0e1..7d6547c 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -6,16 +6,18 @@ services:
       context: .
       dockerfile: Dockerfile
     ports:
-      - "8000:8000"
+      - "8080:8080"
     environment:
-      - DEBUG=false
-      - CORS_ORIGINS=http://localhost:3000,http://localhost:8000
+      - PORT=8080
+      - DEBUG=true
+      - APP_ENV=development
+      - CORS_ORIGINS=http://localhost:3000,http://localhost:5173,http://127.0.0.1:5173,http://localhost:8080
     volumes:
       # Mount data directory for development
       - ./app/data:/app/app/data:ro
     restart: unless-stopped
     healthcheck:
-      test: [ "CMD", "curl", "-f", "http://localhost:8000/" ]
+      test: [ "CMD", "curl", "-f", "http://localhost:8080/" ]
       interval: 30s
       timeout: 10s
       retries: 3
diff --git a/pyproject.toml b/pyproject.toml
index c9477ff..c0e9357 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,19 +1,10 @@
 [project]
 name = "pathways-api"
 version = "0.1.0"
-description = "Pathways API for Open Targets - A comprehensive API for pathway analysis and visualization"
-readme = "README.md"
+description = "FastAPI service for pathway analysis (GSEA) for Open Targets"
 authors = [{ name = "Open Targets", email = "contact@opentargets.org" }]
-license = { text = "Apache-2.0" }
-keywords = ["pathways", "bioinformatics", "api", "open-targets", "gsea", "umap"]
-classifiers = [
-    "Development Status :: 4 - Beta",
-    "Intended Audience :: Science/Research",
-    "License :: OSI Approved :: Apache Software License",
-    "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.12",
-    "Topic :: Scientific/Engineering :: Bio-Informatics",
-]
+readme = "README.md"
+
 
 requires-python = ">=3.12"
 dependencies = [
@@ -24,34 +15,11 @@ dependencies = [
     "uvicorn>=0.32.0",
     "blitzgsea>=1.3.54",
     "pandas>=2.2.3",
-    "umap>=0.1.1",
-    "hdbscan>=0.8.40",
     "numpy>=1.26.4",
     "google-cloud-storage>=3.4.1",
     "pyarrow>=22.0.0",
     "gcsfs>=2025.9.0",
 ]
 
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-[tool.hatch.build.targets.wheel]
-packages = ["app"]
-
 [dependency-groups]
-lint = ["ruff>=0.7.1"]
-dev = [
-    "pytest>=7.0.0",
-    "pytest-asyncio>=0.21.0",
-    "httpx>=0.24.0",
-]
-
-[tool.ruff]
-target-version = "py312"
-line-length = 88
-select = ["E", "F", "W", "C90", "I", "N", "UP", "YTT", "S", "BLE", "FBT", "B", "A", "COM", "C4", "DTZ", "T10", "EM", "EXE", "FA", "ISC", "ICN", "G", "INP", "PIE", "T20", "PYI", "PT", "Q", "RSE", "RET", "SLF", "SIM", "TID", "TCH", "ARG", "PTH", "ERA", "PD", "PGH", "PL", "TRY", "FLY", "NPY", "AIR", "PERF", "FURB", "LOG", "RUF"]
-ignore = ["E501", "S101", "S104", "S105", "S106", "S107"]
-
-[tool.ruff.per-file-ignores]
-"__init__.py" = ["F401"]
+lint = ["ruff>=0.7.1"]
\ No newline at end of file
diff --git a/ui/.env.development b/ui/.env.development
new file mode 100644
index 0000000..e8b2023
--- /dev/null
+++ b/ui/.env.development
@@ -0,0 +1,2 @@
+# Add a .env file for local development
+VITE_API_URL=http://localhost:8000
diff --git a/ui/.env.production b/ui/.env.production
new file mode 100644
index 0000000..460e575
--- /dev/null
+++ b/ui/.env.production
@@ -0,0 +1 @@
+VITE_API_URL=http://localhost:8080
diff --git a/ui/index.html b/ui/index.html
index e4b78ea..53b3037 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -1,13 +1,16 @@
 <!doctype html>
 <html lang="en">
-  <head>
-    <meta charset="UTF-8" />
-    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Vite + React + TS</title>
-  </head>
-  <body>
-    <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
-  </body>
-</html>
+
+<head>
+  <meta charset="UTF-8" />
+  <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>Vite + React + TS</title>
+</head>
+
+<body>
+  <div id="root"></div>
+  <script type="module" src="/src/main.tsx"></script>
+</body>
+
+</html>
\ No newline at end of file
diff --git a/ui/package-lock.json b/ui/package-lock.json
index dbbcba2..ed13c38 100644
--- a/ui/package-lock.json
+++ b/ui/package-lock.json
@@ -19,9 +19,11 @@
         "@mui/icons-material": "^7.2.0",
         "@mui/material": "^7.2.0",
         "@reactflow/background": "^11.3.14",
+        "@types/d3": "^7.4.3",
         "@types/dagre": "^0.7.53",
         "@types/plotly.js": "^3.0.3",
         "@types/react-plotly.js": "^2.6.3",
+        "d3": "^7.9.0",
         "dagre": "^0.8.5",
         "graphql": "^16.11.0",
         "plotly.js-dist": "^3.0.3",
@@ -3667,6 +3669,47 @@
         "node": ">=0.12"
       }
     },
+    "node_modules/d3": {
+      "version": "7.9.0",
+      "resolved": "https://registry.npmjs.org/d3/-/d3-7.9.0.tgz",
+      "integrity": "sha512-e1U46jVP+w7Iut8Jt8ri1YsPOvFpg46k+K8TpCb0P+zjCkjkPnV7WzfDJzMHy1LnA+wj5pLT1wjO901gLXeEhA==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "3",
+        "d3-axis": "3",
+        "d3-brush": "3",
+        "d3-chord": "3",
+        "d3-color": "3",
+        "d3-contour": "4",
+        "d3-delaunay": "6",
+        "d3-dispatch": "3",
+        "d3-drag": "3",
+        "d3-dsv": "3",
+        "d3-ease": "3",
+        "d3-fetch": "3",
+        "d3-force": "3",
+        "d3-format": "3",
+        "d3-geo": "3",
+        "d3-hierarchy": "3",
+        "d3-interpolate": "3",
+        "d3-path": "3",
+        "d3-polygon": "3",
+        "d3-quadtree": "3",
+        "d3-random": "3",
+        "d3-scale": "4",
+        "d3-scale-chromatic": "3",
+        "d3-selection": "3",
+        "d3-shape": "3",
+        "d3-time": "3",
+        "d3-time-format": "4",
+        "d3-timer": "3",
+        "d3-transition": "3",
+        "d3-zoom": "3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/d3-array": {
       "version": "1.2.4",
       "resolved": "https://registry.npmjs.org/d3-array/-/d3-array-1.2.4.tgz",
@@ -3674,6 +3717,43 @@
       "license": "BSD-3-Clause",
       "peer": true
     },
+    "node_modules/d3-axis": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/d3-axis/-/d3-axis-3.0.0.tgz",
+      "integrity": "sha512-IH5tgjV4jE/GhHkRV0HiVYPDtvfjHQlQfJHs0usq7M30XcSBvOotpmH1IgkcXsO/5gEQZD43B//fc7SRT5S+xw==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-brush": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/d3-brush/-/d3-brush-3.0.0.tgz",
+      "integrity": "sha512-ALnjWlVYkXsVIGlOsuWH1+3udkYFI48Ljihfnh8FZPF2QS9o+PzGLBslO0PjzVoHLZ2KCVgAM8NVkXPJB2aNnQ==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-dispatch": "1 - 3",
+        "d3-drag": "2 - 3",
+        "d3-interpolate": "1 - 3",
+        "d3-selection": "3",
+        "d3-transition": "3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-chord": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-chord/-/d3-chord-3.0.1.tgz",
+      "integrity": "sha512-VE5S6TNa+j8msksl7HwjxMHDM2yNK3XCkusIlpX5kwauBfXuyLAtNg9jCp/iHH61tgI4sb6R/EIMWCqEIdjT/g==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-path": "1 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/d3-collection": {
       "version": "1.0.7",
       "resolved": "https://registry.npmjs.org/d3-collection/-/d3-collection-1.0.7.tgz",
@@ -3690,6 +3770,42 @@
         "node": ">=12"
       }
     },
+    "node_modules/d3-contour": {
+      "version": "4.0.2",
+      "resolved": "https://registry.npmjs.org/d3-contour/-/d3-contour-4.0.2.tgz",
+      "integrity": "sha512-4EzFTRIikzs47RGmdxbeUvLWtGedDUNkTcmzoeyg4sP/dvCexO47AaQL7VKy/gul85TOxw+IBgA8US2xwbToNA==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "^3.2.0"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-contour/node_modules/d3-array": {
+      "version": "3.2.4",
+      "resolved": "https://registry.npmjs.org/d3-array/-/d3-array-3.2.4.tgz",
+      "integrity": "sha512-tdQAmyA18i4J7wprpYq8ClcxZy3SC31QMeByyCFyRt7BVHdREQZ5lpzoe5mFEYZUWe+oq8HBvk9JjpibyEV4Jg==",
+      "license": "ISC",
+      "dependencies": {
+        "internmap": "1 - 2"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-delaunay": {
+      "version": "6.0.4",
+      "resolved": "https://registry.npmjs.org/d3-delaunay/-/d3-delaunay-6.0.4.tgz",
+      "integrity": "sha512-mdjtIZ1XLAM8bm/hx3WwjfHt6Sggek7qH043O8KEjDXN40xi3vx/6pYSVTwLjEgiXQTbvaouWKynLBiUZ6SK6A==",
+      "license": "ISC",
+      "dependencies": {
+        "delaunator": "5"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/d3-dispatch": {
       "version": "3.0.1",
       "resolved": "https://registry.npmjs.org/d3-dispatch/-/d3-dispatch-3.0.1.tgz",
@@ -3712,6 +3828,52 @@
         "node": ">=12"
       }
     },
+    "node_modules/d3-dsv": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-dsv/-/d3-dsv-3.0.1.tgz",
+      "integrity": "sha512-UG6OvdI5afDIFP9w4G0mNq50dSOsXHJaRE8arAS5o9ApWnIElp8GZw1Dun8vP8OyHOZ/QJUKUJwxiiCCnUwm+Q==",
+      "license": "ISC",
+      "dependencies": {
+        "commander": "7",
+        "iconv-lite": "0.6",
+        "rw": "1"
+      },
+      "bin": {
+        "csv2json": "bin/dsv2json.js",
+        "csv2tsv": "bin/dsv2dsv.js",
+        "dsv2dsv": "bin/dsv2dsv.js",
+        "dsv2json": "bin/dsv2json.js",
+        "json2csv": "bin/json2dsv.js",
+        "json2dsv": "bin/json2dsv.js",
+        "json2tsv": "bin/json2dsv.js",
+        "tsv2csv": "bin/dsv2dsv.js",
+        "tsv2json": "bin/dsv2json.js"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-dsv/node_modules/commander": {
+      "version": "7.2.0",
+      "resolved": "https://registry.npmjs.org/commander/-/commander-7.2.0.tgz",
+      "integrity": "sha512-QrWXB+ZQSVPmIWIhtEO9H+gwHaMGYiF5ChvoJ+K9ZGHG/sVsa6yiesAD1GC/x46sET00Xlwo1u49RVVVzvcSkw==",
+      "license": "MIT",
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/d3-dsv/node_modules/iconv-lite": {
+      "version": "0.6.3",
+      "resolved": "https://registry.npmjs.org/iconv-lite/-/iconv-lite-0.6.3.tgz",
+      "integrity": "sha512-4fCk79wshMdzMp2rH06qWrJE4iolqLhCUH+OiuIgU++RB0+94NlDL81atO7GX55uUKueo0txHNtvEyI6D7WdMw==",
+      "license": "MIT",
+      "dependencies": {
+        "safer-buffer": ">= 2.1.2 < 3.0.0"
+      },
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
     "node_modules/d3-ease": {
       "version": "3.0.1",
       "resolved": "https://registry.npmjs.org/d3-ease/-/d3-ease-3.0.1.tgz",
@@ -3721,6 +3883,18 @@
         "node": ">=12"
       }
     },
+    "node_modules/d3-fetch": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-fetch/-/d3-fetch-3.0.1.tgz",
+      "integrity": "sha512-kpkQIM20n3oLVBKGg6oHrUchHM3xODkTzjMoj7aWQFq5QEM+R6E4WkzT5+tojDY7yjez8KgCBRoj4aEr99Fdqw==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-dsv": "1 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/d3-force": {
       "version": "1.2.1",
       "resolved": "https://registry.npmjs.org/d3-force/-/d3-force-1.2.1.tgz",
@@ -3752,8 +3926,7 @@
       "version": "1.4.5",
       "resolved": "https://registry.npmjs.org/d3-format/-/d3-format-1.4.5.tgz",
       "integrity": "sha512-J0piedu6Z8iB6TbIGfZgDzfXxUFN3qQRMofy2oPdXzQibYGqPB/9iMcxr/TGalU+2RsyDO+U4f33id8tbnSRMQ==",
-      "license": "BSD-3-Clause",
-      "peer": true
+      "license": "BSD-3-Clause"
     },
     "node_modules/d3-geo": {
       "version": "1.12.1",
@@ -3808,8 +3981,16 @@
       "version": "1.0.9",
       "resolved": "https://registry.npmjs.org/d3-path/-/d3-path-1.0.9.tgz",
       "integrity": "sha512-VLaYcn81dtHVTjEHd8B+pbe9yHWpXKZUC87PzoFmsFrJqgFwDe/qxfp5MlfsfM1V5E/iVt0MmEbWQ7FVIXh/bg==",
-      "license": "BSD-3-Clause",
-      "peer": true
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/d3-polygon": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-polygon/-/d3-polygon-3.0.1.tgz",
+      "integrity": "sha512-3vbA7vXYwfe1SYhED++fPUQlWSYTTGmFmQiany/gdbiWgU/iEyQzyymwL9SkJjFFuCS4902BSzewVGsHHmHtXg==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
     },
     "node_modules/d3-quadtree": {
       "version": "1.0.7",
@@ -3818,6 +3999,68 @@
       "license": "BSD-3-Clause",
       "peer": true
     },
+    "node_modules/d3-random": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-random/-/d3-random-3.0.1.tgz",
+      "integrity": "sha512-FXMe9GfxTxqd5D6jFsQ+DJ8BJS4E/fT5mqqdjovykEB2oFbTMDVdg1MGFxfQW+FBOGoB++k8swBrgwSHT1cUXQ==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-scale": {
+      "version": "4.0.2",
+      "resolved": "https://registry.npmjs.org/d3-scale/-/d3-scale-4.0.2.tgz",
+      "integrity": "sha512-GZW464g1SH7ag3Y7hXjf8RoUuAFIqklOAq3MRl4OaWabTFJY9PN/E1YklhXLh+OQ3fM9yS2nOkCoS+WLZ6kvxQ==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "2.10.0 - 3",
+        "d3-format": "1 - 3",
+        "d3-interpolate": "1.2.0 - 3",
+        "d3-time": "2.1.1 - 3",
+        "d3-time-format": "2 - 4"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-scale-chromatic": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/d3-scale-chromatic/-/d3-scale-chromatic-3.1.0.tgz",
+      "integrity": "sha512-A3s5PWiZ9YCXFye1o246KoscMWqf8BsD9eRiJ3He7C9OBaxKhAd5TFCdEx/7VbKtxxTsu//1mMJFrEt572cEyQ==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-color": "1 - 3",
+        "d3-interpolate": "1 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-scale/node_modules/d3-array": {
+      "version": "3.2.4",
+      "resolved": "https://registry.npmjs.org/d3-array/-/d3-array-3.2.4.tgz",
+      "integrity": "sha512-tdQAmyA18i4J7wprpYq8ClcxZy3SC31QMeByyCFyRt7BVHdREQZ5lpzoe5mFEYZUWe+oq8HBvk9JjpibyEV4Jg==",
+      "license": "ISC",
+      "dependencies": {
+        "internmap": "1 - 2"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3-scale/node_modules/d3-time": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/d3-time/-/d3-time-3.1.0.tgz",
+      "integrity": "sha512-VqKjzBLejbSMT4IgbmVgDjpkYrNWUYJnbCGo874u7MMKIWsILRX+OpX/gTk8MqjpT1A/c6HY2dCA77ZN0lkQ2Q==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "2 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/d3-selection": {
       "version": "3.0.0",
       "resolved": "https://registry.npmjs.org/d3-selection/-/d3-selection-3.0.0.tgz",
@@ -3841,15 +4084,13 @@
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/d3-time/-/d3-time-1.1.0.tgz",
       "integrity": "sha512-Xh0isrZ5rPYYdqhAVk8VLnMEidhz5aP7htAADH6MfzgmmicPkTo8LhkLxci61/lCB7n7UmE3bN0leRt+qvkLxA==",
-      "license": "BSD-3-Clause",
-      "peer": true
+      "license": "BSD-3-Clause"
     },
     "node_modules/d3-time-format": {
       "version": "2.3.0",
       "resolved": "https://registry.npmjs.org/d3-time-format/-/d3-time-format-2.3.0.tgz",
       "integrity": "sha512-guv6b2H37s2Uq/GefleCDtbe0XZAuy7Wa49VGkPVPMfLL9qObgBST3lEHJBMUp8S7NdLQAGIvr2KXk8Hc98iKQ==",
       "license": "BSD-3-Clause",
-      "peer": true,
       "dependencies": {
         "d3-time": "1"
       }
@@ -3898,6 +4139,116 @@
         "node": ">=12"
       }
     },
+    "node_modules/d3/node_modules/d3-array": {
+      "version": "3.2.4",
+      "resolved": "https://registry.npmjs.org/d3-array/-/d3-array-3.2.4.tgz",
+      "integrity": "sha512-tdQAmyA18i4J7wprpYq8ClcxZy3SC31QMeByyCFyRt7BVHdREQZ5lpzoe5mFEYZUWe+oq8HBvk9JjpibyEV4Jg==",
+      "license": "ISC",
+      "dependencies": {
+        "internmap": "1 - 2"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-force": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/d3-force/-/d3-force-3.0.0.tgz",
+      "integrity": "sha512-zxV/SsA+U4yte8051P4ECydjD/S+qeYtnaIyAs9tgHCqfguma/aAQDjo85A9Z6EKhBirHRJHXIgJUlffT4wdLg==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-dispatch": "1 - 3",
+        "d3-quadtree": "1 - 3",
+        "d3-timer": "1 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-format": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/d3-format/-/d3-format-3.1.0.tgz",
+      "integrity": "sha512-YyUI6AEuY/Wpt8KWLgZHsIU86atmikuoOmCfommt0LYHiQSPjvX2AcFc38PX0CBpr2RCyZhjex+NS/LPOv6YqA==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-geo": {
+      "version": "3.1.1",
+      "resolved": "https://registry.npmjs.org/d3-geo/-/d3-geo-3.1.1.tgz",
+      "integrity": "sha512-637ln3gXKXOwhalDzinUgY83KzNWZRKbYubaG+fGVuc/dxO64RRljtCTnf5ecMyE1RIdtqpkVcq0IbtU2S8j2Q==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "2.5.0 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-hierarchy": {
+      "version": "3.1.2",
+      "resolved": "https://registry.npmjs.org/d3-hierarchy/-/d3-hierarchy-3.1.2.tgz",
+      "integrity": "sha512-FX/9frcub54beBdugHjDCdikxThEqjnR93Qt7PvQTOHxyiNCAlvMrHhclk3cD5VeAaq9fxmfRp+CnWw9rEMBuA==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-path": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/d3-path/-/d3-path-3.1.0.tgz",
+      "integrity": "sha512-p3KP5HCf/bvjBSSKuXid6Zqijx7wIfNW+J/maPs+iwR35at5JCbLUT0LzF1cnjbCHWhqzQTIN2Jpe8pRebIEFQ==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-quadtree": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/d3-quadtree/-/d3-quadtree-3.0.1.tgz",
+      "integrity": "sha512-04xDrxQTDTCFwP5H6hRhsRcb9xxv2RzkcsygFzmkSIOJy3PeRJP7sNk3VRIbKXcog561P9oU0/rVH6vDROAgUw==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-shape": {
+      "version": "3.2.0",
+      "resolved": "https://registry.npmjs.org/d3-shape/-/d3-shape-3.2.0.tgz",
+      "integrity": "sha512-SaLBuwGm3MOViRq2ABk3eLoxwZELpH6zhl3FbAoJ7Vm1gofKx6El1Ib5z23NUEhF9AsGl7y+dzLe5Cw2AArGTA==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-path": "^3.1.0"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-time": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/d3-time/-/d3-time-3.1.0.tgz",
+      "integrity": "sha512-VqKjzBLejbSMT4IgbmVgDjpkYrNWUYJnbCGo874u7MMKIWsILRX+OpX/gTk8MqjpT1A/c6HY2dCA77ZN0lkQ2Q==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-array": "2 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/d3/node_modules/d3-time-format": {
+      "version": "4.1.0",
+      "resolved": "https://registry.npmjs.org/d3-time-format/-/d3-time-format-4.1.0.tgz",
+      "integrity": "sha512-dJxPBlzC7NugB2PDLwo9Q8JiTR3M3e4/XANkreKSUxF8vvXKqm1Yfq4Q5dl8budlunRVlUUaDUgFt7eA8D6NLg==",
+      "license": "ISC",
+      "dependencies": {
+        "d3-time": "1 - 3"
+      },
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/dagre": {
       "version": "0.8.5",
       "resolved": "https://registry.npmjs.org/dagre/-/dagre-0.8.5.tgz",
@@ -3942,6 +4293,15 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/delaunator": {
+      "version": "5.0.1",
+      "resolved": "https://registry.npmjs.org/delaunator/-/delaunator-5.0.1.tgz",
+      "integrity": "sha512-8nvh+XBe96aCESrGOqMp/84b13H9cdKbG5P2ejQCh4d4sK9RL4371qou9drQjMhvnPmhWl5hnmqbEE0fXr9Xnw==",
+      "license": "ISC",
+      "dependencies": {
+        "robust-predicates": "^3.0.2"
+      }
+    },
     "node_modules/detect-kerning": {
       "version": "2.1.2",
       "resolved": "https://registry.npmjs.org/detect-kerning/-/detect-kerning-2.1.2.tgz",
@@ -5247,6 +5607,15 @@
         "node": "^14.17.0 || ^16.13.0 || >=18.0.0"
       }
     },
+    "node_modules/internmap": {
+      "version": "2.0.3",
+      "resolved": "https://registry.npmjs.org/internmap/-/internmap-2.0.3.tgz",
+      "integrity": "sha512-5Hh7Y1wQbvY5ooGgPbDaL5iYLAPzMTUrjMulskHLH6wnv/A+1q5rgEaiuqEjB+oxGXIVZs1FF+R/KPN3ZSQYYg==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=12"
+      }
+    },
     "node_modules/is-arrayish": {
       "version": "0.2.1",
       "resolved": "https://registry.npmjs.org/is-arrayish/-/is-arrayish-0.2.1.tgz",
@@ -6708,6 +7077,12 @@
       "license": "MIT",
       "peer": true
     },
+    "node_modules/robust-predicates": {
+      "version": "3.0.2",
+      "resolved": "https://registry.npmjs.org/robust-predicates/-/robust-predicates-3.0.2.tgz",
+      "integrity": "sha512-IXgzBWvWQwE6PrDI05OvmXUIruQTcoMDzRsOd5CDvHCVLcLHMTSYvOK5Cm46kWqlV3yAbuSpBZdJ5oP5OUoStg==",
+      "license": "Unlicense"
+    },
     "node_modules/rollup": {
       "version": "4.46.2",
       "resolved": "https://registry.npmjs.org/rollup/-/rollup-4.46.2.tgz",
@@ -6776,8 +7151,7 @@
       "version": "1.3.3",
       "resolved": "https://registry.npmjs.org/rw/-/rw-1.3.3.tgz",
       "integrity": "sha512-PdhdWy89SiZogBLaw42zdeqtRJ//zFd2PgQavcICDUgJT5oW10QCRKbJ6bg4r0/UY2M6BWd5tkxuGFRvCkgfHQ==",
-      "license": "BSD-3-Clause",
-      "peer": true
+      "license": "BSD-3-Clause"
     },
     "node_modules/safe-buffer": {
       "version": "5.2.1",
@@ -6804,8 +7178,7 @@
       "version": "2.1.2",
       "resolved": "https://registry.npmjs.org/safer-buffer/-/safer-buffer-2.1.2.tgz",
       "integrity": "sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg==",
-      "license": "MIT",
-      "peer": true
+      "license": "MIT"
     },
     "node_modules/sax": {
       "version": "1.4.1",
diff --git a/ui/package.json b/ui/package.json
index f78631a..59a99b8 100644
--- a/ui/package.json
+++ b/ui/package.json
@@ -21,9 +21,11 @@
     "@mui/icons-material": "^7.2.0",
     "@mui/material": "^7.2.0",
     "@reactflow/background": "^11.3.14",
+    "@types/d3": "^7.4.3",
     "@types/dagre": "^0.7.53",
     "@types/plotly.js": "^3.0.3",
     "@types/react-plotly.js": "^2.6.3",
+    "d3": "^7.9.0",
     "dagre": "^0.8.5",
     "graphql": "^16.11.0",
     "plotly.js-dist": "^3.0.3",
diff --git a/ui/src/components/flame-graph/D3SunburstChart.tsx b/ui/src/components/flame-graph/D3SunburstChart.tsx
new file mode 100644
index 0000000..6801c74
--- /dev/null
+++ b/ui/src/components/flame-graph/D3SunburstChart.tsx
@@ -0,0 +1,322 @@
+import React, { useEffect, useRef, useMemo } from "react";
+import * as d3 from "d3";
+import { Box } from "@mui/material";
+import type { Pathway } from "../../lib/api";
+import { buildPathwayHierarchy, getEffectiveRootPathways } from "../../utils/pathwayHierarchy";
+import { 
+  PRIORITISATION_COLORS, 
+  mapToPrioritizationColor, 
+  ROOT_NODE_COLORS
+} from "../../utils/colorPalettes";
+
+interface D3SunburstChartProps {
+  pathways: Pathway[];
+  maxPathways: number;
+  orientation: "h" | "v";
+  branchvalues: "total" | "remainder";
+}
+
+interface D3Node extends d3.HierarchyNode<any> {
+  data: {
+    id: string;
+    name: string;
+    pathway?: Pathway;
+    pValue?: number;
+    fdr?: number;
+    nes?: number;
+    geneCount?: number;
+    genes?: string[];
+    type: "root" | "pathway";
+  };
+}
+
+const D3SunburstChart: React.FC<D3SunburstChartProps> = ({
+  pathways,
+  maxPathways,
+  orientation,
+  branchvalues,
+}) => {
+  const svgRef = useRef<SVGSVGElement>(null);
+  const containerRef = useRef<HTMLDivElement>(null);
+
+  // Convert pathway data to D3 hierarchy format
+  const hierarchyData = useMemo(() => {
+    if (pathways.length === 0) return null;
+
+    const limitedPathways = pathways.slice(0, maxPathways);
+    const { pathwayMap, childrenMap } = buildPathwayHierarchy(limitedPathways);
+    const rootPathways = getEffectiveRootPathways(limitedPathways);
+
+    // Collect all NES values for color scaling
+    const allNESValues: number[] = [];
+    limitedPathways.forEach((pathway) => {
+      const nes = pathway["NES"] || pathway["nes"] || 0;
+      allNESValues.push(nes);
+    });
+
+    const maxNES = Math.max(...allNESValues);
+    const minNES = Math.min(...allNESValues);
+
+    // Helper function to create node data
+    const createNodeData = (pathway: Pathway, type: "root" | "pathway") => {
+      const pValue = pathway["p-value"] || pathway["p_value"] || pathway["pvalue"];
+      const fdr = pathway["FDR"] || pathway["fdr"];
+      const nes = pathway["NES"] || pathway["nes"];
+      const genes = pathway["Leading edge genes"] || pathway["genes"] || [];
+      const geneCount = Array.isArray(genes)
+        ? genes.length
+        : typeof genes === "string"
+          ? genes.split(",").length
+          : 0;
+
+      // Calculate value based on significance (more significant = larger)
+      const significance = 1 / (pValue || 1);
+      const value = Math.max(1, Math.log(significance) * 5);
+
+      return {
+        id: pathway["ID"] || pathway["id"] || "",
+        name: pathway["Pathway"] || pathway["pathway"] || "",
+        pathway,
+        pValue,
+        fdr,
+        nes,
+        geneCount,
+        genes: Array.isArray(genes)
+          ? genes
+          : typeof genes === "string"
+            ? genes.split(",").map((g: string) => g.trim())
+            : [],
+        type,
+        value,
+        color: type === "root" 
+          ? ROOT_NODE_COLORS.primary 
+          : mapToPrioritizationColor(nes || 0, minNES, maxNES)
+      };
+    };
+
+    // Build hierarchy structure
+    const buildHierarchy = (parentId: string, processedIds: Set<string>): any[] => {
+      const children = childrenMap.get(parentId) || [];
+      return children
+        .filter(childId => !processedIds.has(childId))
+        .map(childId => {
+          processedIds.add(childId);
+          const pathway = pathwayMap.get(childId);
+          if (!pathway) return null;
+
+          const nodeData = createNodeData(pathway, "pathway");
+          const childNodes = buildHierarchy(childId, processedIds);
+
+          return {
+            ...nodeData,
+            children: childNodes.length > 0 ? childNodes : undefined
+          };
+        })
+        .filter(Boolean);
+    };
+
+    // Create root node
+    const rootNodeData = {
+      id: "root",
+      name: "All Pathways",
+      type: "root" as const,
+      value: limitedPathways.length,
+      color: ROOT_NODE_COLORS.primary,
+      children: rootPathways.map(pathway => {
+        const pathwayId = pathway["ID"] || pathway["id"] || "";
+        const nodeData = createNodeData(pathway, "pathway");
+        const processedIds = new Set<string>();
+        processedIds.add(pathwayId);
+        
+        const childNodes = buildHierarchy(pathwayId, processedIds);
+        
+        return {
+          ...nodeData,
+          children: childNodes.length > 0 ? childNodes : undefined
+        };
+      })
+    };
+
+    return rootNodeData;
+  }, [pathways, maxPathways]);
+
+  // D3 rendering function
+  const renderSunburst = () => {
+    if (!hierarchyData || !svgRef.current || !containerRef.current) return;
+
+    const container = containerRef.current;
+    const svg = d3.select(svgRef.current);
+    
+    // Clear previous content
+    svg.selectAll("*").remove();
+
+    const width = container.clientWidth;
+    const height = 700;
+    const radius = Math.min(width, height) / 2 - 10;
+
+    // Set up SVG
+    svg
+      .attr("width", width)
+      .attr("height", height)
+      .style("background-color", "white");
+
+    // Create main group
+    const g = svg
+      .append("g")
+      .attr("transform", `translate(${width / 2},${height / 2})`);
+
+    // Create partition layout
+    const partition = d3.partition()
+      .size([2 * Math.PI, radius]);
+
+    // Create arc generator
+    const arc = d3.arc<D3Node>()
+      .startAngle(d => d.x0)
+      .endAngle(d => d.x1)
+      .padAngle(d => Math.min((d.x1 - d.x0) / 2, 0.005))
+      .padRadius(radius / 2)
+      .innerRadius(d => d.y0)
+      .outerRadius(d => d.y1 - 1);
+
+    // Create hierarchy
+    const root = d3.hierarchy(hierarchyData)
+      .sum(d => d.value)
+      .sort((a, b) => (b.value || 0) - (a.value || 0));
+
+    const nodes = partition(root).descendants().filter(d => d.x1 - d.x0 > 0.005);
+
+    // Create arcs
+    const arcs = g
+      .selectAll(".arc")
+      .data(nodes)
+      .enter()
+      .append("path")
+      .attr("class", "arc")
+      .attr("d", arc)
+      .style("fill", d => d.data.color)
+      .style("cursor", "pointer")
+      .style("opacity", 0)
+      .on("mouseover", function(event, d) {
+        // Highlight current path
+        const sequenceArray = d.ancestors().reverse();
+        
+        // Fade all arcs
+        arcs.transition().duration(300).style("opacity", 0.3);
+        
+        // Highlight current path
+        arcs
+          .filter(d => sequenceArray.indexOf(d) >= 0)
+          .transition()
+          .duration(300)
+          .style("opacity", 1);
+
+        // Show tooltip (you can implement this based on your tooltip system)
+        showTooltip(event, d);
+      })
+      .on("mouseleave", function() {
+        // Reset all arcs
+        arcs.transition().duration(300).style("opacity", 1);
+        hideTooltip();
+      })
+      .on("click", function(event, d) {
+        // Handle click events if needed
+        console.log("Clicked:", d.data);
+      });
+
+    // Animate arcs
+    arcs
+      .transition()
+      .delay((d, i) => i * 20)
+      .style("opacity", 1);
+
+    // Add labels for larger arcs
+    const labels = g
+      .selectAll(".label")
+      .data(nodes.filter(d => d.x1 - d.x0 > 0.1 && d.y1 - d.y0 > 10))
+      .enter()
+      .append("text")
+      .attr("class", "label")
+      .attr("transform", d => {
+        const x = (d.x0 + d.x1) / 2 * 180 / Math.PI;
+        const y = (d.y0 + d.y1) / 2;
+        return `rotate(${x - 90}) translate(${y},0) rotate(${x < 180 ? 0 : 180})`;
+      })
+      .attr("text-anchor", "middle")
+      .attr("dy", "0.35em")
+      .style("font-size", "12px")
+      .style("font-family", "Arial, sans-serif")
+      .style("fill", "#333")
+      .text(d => d.data.name.length > 15 ? d.data.name.substring(0, 15) + "..." : d.data.name)
+      .style("opacity", 0)
+      .transition()
+      .delay((d, i) => i * 20 + 200)
+      .style("opacity", 1);
+  };
+
+  // Tooltip functions
+  const showTooltip = (event: MouseEvent, d: D3Node) => {
+    const tooltip = d3.select("body")
+      .append("div")
+      .attr("class", "sunburst-tooltip")
+      .style("position", "absolute")
+      .style("background", "rgba(0, 0, 0, 0.8)")
+      .style("color", "white")
+      .style("padding", "8px")
+      .style("border-radius", "4px")
+      .style("font-size", "12px")
+      .style("pointer-events", "none")
+      .style("z-index", "1000");
+
+    const content = `
+      <div><strong>${d.data.name}</strong></div>
+      ${d.data.type === "pathway" ? `
+        <div>NES: ${d.data.nes?.toFixed(3) || "N/A"}</div>
+        <div>P-value: ${d.data.pValue?.toExponential(2) || "N/A"}</div>
+        <div>FDR: ${d.data.fdr?.toExponential(2) || "N/A"}</div>
+        <div>Genes: ${d.data.geneCount || 0}</div>
+      ` : ""}
+    `;
+
+    tooltip.html(content);
+
+    tooltip
+      .style("left", (event.pageX + 10) + "px")
+      .style("top", (event.pageY - 10) + "px");
+  };
+
+  const hideTooltip = () => {
+    d3.selectAll(".sunburst-tooltip").remove();
+  };
+
+  // Render on mount and when data changes
+  useEffect(() => {
+    renderSunburst();
+  }, [hierarchyData]);
+
+  // Handle resize
+  useEffect(() => {
+    const handleResize = () => {
+      renderSunburst();
+    };
+
+    window.addEventListener("resize", handleResize);
+    return () => window.removeEventListener("resize", handleResize);
+  }, [hierarchyData]);
+
+  if (pathways.length === 0) {
+    return null;
+  }
+
+  return (
+    <Box sx={{ flex: 1, position: "relative", minHeight: "600px" }}>
+      <div 
+        ref={containerRef} 
+        style={{ width: "100%", height: "100%" }}
+      >
+        <svg ref={svgRef} />
+      </div>
+    </Box>
+  );
+};
+
+export default D3SunburstChart;
diff --git a/ui/src/components/flame-graph/PathwaysFlameGraph.tsx b/ui/src/components/flame-graph/PathwaysFlameGraph.tsx
index 4ed4618..2c896d7 100644
--- a/ui/src/components/flame-graph/PathwaysFlameGraph.tsx
+++ b/ui/src/components/flame-graph/PathwaysFlameGraph.tsx
@@ -3,10 +3,12 @@ import { Box, Tabs, Tab, Typography, Button } from "@mui/material";
 import {
 	DonutLarge as SunburstIcon,
 	ShowChart as BarChartIcon,
+	DonutLarge as D3SunburstIcon,
 } from "@mui/icons-material";
 import type { Pathway } from "../../lib/api";
 import FlameGraphHeader from "./FlameGraphHeader";
 import SunburstChart from "./SunburstChart";
+import D3SunburstChart from "./D3SunburstChart";
 import HorizontalFlameChart from "./HorizontalFlameChart";
 import FlameGraphSettings from "./FlameGraphSettings";
 import PathwayFilter, { type PathwayFilters } from "./PathwayFilter";
@@ -233,7 +235,12 @@ const PathwaysFlameGraph: React.FC<PathwaysFlameGraphProps> = ({
 						>
 							<Tab
 								icon={<SunburstIcon />}
-								label="Sunburst"
+								label="Plotly Sunburst"
+								iconPosition="start"
+							/>
+							<Tab
+								icon={<D3SunburstIcon />}
+								label="D3 Sunburst"
 								iconPosition="start"
 							/>
 							<Tab
@@ -255,7 +262,7 @@ const PathwaysFlameGraph: React.FC<PathwaysFlameGraphProps> = ({
 							minHeight: "500px",
 						}}
 					>
-						{/* Sunburst Chart */}
+						{/* Plotly Sunburst Chart */}
 						{activeTab === 0 && (
 							<Box sx={{ flex: 1, minHeight: "500px" }}>
 								<SunburstChart
@@ -267,8 +274,20 @@ const PathwaysFlameGraph: React.FC<PathwaysFlameGraphProps> = ({
 							</Box>
 						)}
 
-						{/* Horizontal Flame Graph Chart */}
+						{/* D3 Sunburst Chart */}
 						{activeTab === 1 && (
+							<Box sx={{ flex: 1, minHeight: "500px" }}>
+								<D3SunburstChart
+									pathways={filteredPathways}
+									maxPathways={settings.maxPathways}
+									orientation={settings.orientation}
+									branchvalues={settings.branchvalues}
+								/>
+							</Box>
+						)}
+
+						{/* Horizontal Flame Graph Chart */}
+						{activeTab === 2 && (
 							<Box sx={{ flex: 1, minHeight: "500px" }}>
 								<HorizontalFlameChart
 									pathways={filteredPathways}
diff --git a/ui/src/components/flame-graph/index.ts b/ui/src/components/flame-graph/index.ts
index b33c3e1..cb10d96 100644
--- a/ui/src/components/flame-graph/index.ts
+++ b/ui/src/components/flame-graph/index.ts
@@ -1,5 +1,6 @@
 export { default as PathwaysFlameGraph } from "./PathwaysFlameGraph";
 export { default as FlameGraphHeader } from "./FlameGraphHeader";
 export { default as SunburstChart } from "./SunburstChart";
+export { default as D3SunburstChart } from "./D3SunburstChart";
 export { default as HorizontalFlameChart } from "./HorizontalFlameChart";
 export { default as FlameGraphSettings } from "./FlameGraphSettings"; 
\ No newline at end of file
diff --git a/ui/src/data/mockPathwayData.ts b/ui/src/data/mockPathwayData.ts
new file mode 100644
index 0000000..89e253f
--- /dev/null
+++ b/ui/src/data/mockPathwayData.ts
@@ -0,0 +1,123 @@
+// Mock pathway data for testing D3 sunburst component
+export const mockPathwayData = [
+  {
+    "ID": "R-HSA-109582",
+    "Pathway": "Hemostasis",
+    "ES": 0.347,
+    "NES": 2.892,
+    "FDR": 0.188,
+    "p-value": 0.0038,
+    "Number of input genes": 40,
+    "Leading edge genes": "GATA3,MYB,ABL1,NRAS,PTPN11,IRF1,RASGRP1",
+    "Pathway size": 706,
+    "Parent pathway": ""
+  },
+  {
+    "ID": "R-HSA-109583",
+    "Pathway": "Blood Coagulation",
+    "ES": 0.298,
+    "NES": 2.156,
+    "FDR": 0.245,
+    "p-value": 0.0072,
+    "Number of input genes": 32,
+    "Leading edge genes": "F2,F7,F8,F9,F10,F11,F12",
+    "Pathway size": 156,
+    "Parent pathway": "R-HSA-109582"
+  },
+  {
+    "ID": "R-HSA-109584",
+    "Pathway": "Platelet Activation",
+    "ES": 0.267,
+    "NES": 1.987,
+    "FDR": 0.312,
+    "p-value": 0.0125,
+    "Number of input genes": 28,
+    "Leading edge genes": "GP1BA,GP1BB,GP9,ITGA2B,ITGB3",
+    "Pathway size": 89,
+    "Parent pathway": "R-HSA-109582"
+  },
+  {
+    "ID": "R-HSA-109585",
+    "Pathway": "Fibrinolysis",
+    "ES": 0.234,
+    "NES": 1.756,
+    "FDR": 0.389,
+    "p-value": 0.0187,
+    "Number of input genes": 24,
+    "Leading edge genes": "PLG,PLAU,PLAT,SERPINE1",
+    "Pathway size": 67,
+    "Parent pathway": "R-HSA-109582"
+  },
+  {
+    "ID": "R-HSA-109586",
+    "Pathway": "Immune Response",
+    "ES": 0.412,
+    "NES": 3.124,
+    "FDR": 0.156,
+    "p-value": 0.0023,
+    "Number of input genes": 45,
+    "Leading edge genes": "IL2,IL4,IL6,IL10,IFNG,TNF",
+    "Pathway size": 892,
+    "Parent pathway": ""
+  },
+  {
+    "ID": "R-HSA-109587",
+    "Pathway": "T Cell Activation",
+    "ES": 0.356,
+    "NES": 2.678,
+    "FDR": 0.201,
+    "p-value": 0.0045,
+    "Number of input genes": 38,
+    "Leading edge genes": "CD3D,CD3E,CD3G,CD4,CD8A",
+    "Pathway size": 234,
+    "Parent pathway": "R-HSA-109586"
+  },
+  {
+    "ID": "R-HSA-109588",
+    "Pathway": "B Cell Activation",
+    "ES": 0.289,
+    "NES": 2.234,
+    "FDR": 0.278,
+    "p-value": 0.0089,
+    "Number of input genes": 31,
+    "Leading edge genes": "CD19,CD20,CD21,CD22,CD79A",
+    "Pathway size": 178,
+    "Parent pathway": "R-HSA-109586"
+  },
+  {
+    "ID": "R-HSA-109589",
+    "Pathway": "Metabolism",
+    "ES": 0.198,
+    "NES": 1.456,
+    "FDR": 0.445,
+    "p-value": 0.0234,
+    "Number of input genes": 22,
+    "Leading edge genes": "GLUT1,GLUT2,GLUT3,GLUT4",
+    "Pathway size": 456,
+    "Parent pathway": ""
+  },
+  {
+    "ID": "R-HSA-109590",
+    "Pathway": "Glycolysis",
+    "ES": 0.167,
+    "NES": 1.234,
+    "FDR": 0.512,
+    "p-value": 0.0345,
+    "Number of input genes": 19,
+    "Leading edge genes": "HK1,HK2,PFKM,ALDOA,ENO1",
+    "Pathway size": 123,
+    "Parent pathway": "R-HSA-109589"
+  },
+  {
+    "ID": "R-HSA-109591",
+    "Pathway": "Oxidative Phosphorylation",
+    "ES": 0.145,
+    "NES": 1.089,
+    "FDR": 0.567,
+    "p-value": 0.0456,
+    "Number of input genes": 16,
+    "Leading edge genes": "NDUFA1,NDUFA2,NDUFA3,NDUFA4",
+    "Pathway size": 98,
+    "Parent pathway": "R-HSA-109589"
+  }
+];
diff --git a/ui/src/lib/api.ts b/ui/src/lib/api.ts
index 8422402..b46809f 100644
--- a/ui/src/lib/api.ts
+++ b/ui/src/lib/api.ts
@@ -1,4 +1,14 @@
-const API_BASE_URL = 'http://localhost:8000';
+const getApiBaseUrl = () => {
+  // For production (when served from the same domain)
+  if (window.location.hostname !== 'localhost' && window.location.hostname !== '127.0.0.1') {
+    return ''; // Use relative URLs in production
+  }
+
+  // For local development
+  return import.meta.env.VITE_API_URL || 'http://localhost:8000';
+};
+
+const API_BASE_URL = getApiBaseUrl();
 
 export type Pathway = Record<string, any>;
 
@@ -65,12 +75,12 @@ class ApiClient {
     }
   }
 
-  // GSEA endpoint
+  // GSEA endpoint - file upload
   async runGsea(params: GseaParams): Promise<ApiResponse<Pathway[]>> {
     const formData = new FormData();
     formData.append('tsv_file', params.tsv_file);
 
-    return this.request<Pathway[]>(`/api/gsea?gmt_name=${encodeURIComponent(params.gmt_name)}`, {
+    return this.request<Pathway[]>(`/api/gsea/analyze/file?gmt_name=${encodeURIComponent(params.gmt_name)}`, {
       method: 'POST',
       body: formData,
       headers: {}, // Let the browser set the Content-Type for FormData
diff --git a/ui/src/pages/Pathways.tsx b/ui/src/pages/Pathways.tsx
index cd12dc0..8987599 100644
--- a/ui/src/pages/Pathways.tsx
+++ b/ui/src/pages/Pathways.tsx
@@ -9,15 +9,19 @@ import {
 	MenuItem,
 	Button,
 	Alert,
+	Switch,
+	FormControlLabel,
 } from "@mui/material";
 import { CloudUpload } from "@mui/icons-material";
 import { useGsea, useGmtLibraries } from "../hooks/useApi";
 import PathwaysResults from "../components/PathwaysResults";
+import { mockPathwayData } from "../data/mockPathwayData";
 
 const Pathways: React.FC = () => {
 	const [selectedFile, setSelectedFile] = useState<File | null>(null);
 	const [library, setLibrary] = useState<string>("");
 	const [fileError, setFileError] = useState<string>("");
+	const [testMode, setTestMode] = useState<boolean>(false);
 
 	const {
 		data: gmtLibraries,
@@ -32,7 +36,10 @@ const Pathways: React.FC = () => {
 		execute: runGsea,
 	} = useGsea();
 
-	console.log({pathways});
+	// Use mock data in test mode, otherwise use real data
+	const displayPathways = testMode ? mockPathwayData : pathways;
+	const displayLoading = testMode ? false : loading;
+	const displayError = testMode ? null : error;
 
 	// Set default library when libraries are loaded
 	React.useEffect(() => {
@@ -91,7 +98,7 @@ const Pathways: React.FC = () => {
 								value={library}
 								label="GMT Library"
 								onChange={(e) => setLibrary(e.target.value)}
-								disabled={librariesLoading}
+								disabled={librariesLoading || testMode}
 							>
 								{gmtLibraries?.map((lib) => (
 									<MenuItem key={lib} value={lib}>
@@ -115,6 +122,7 @@ const Pathways: React.FC = () => {
 							id="tsv-file-upload"
 							type="file"
 							onChange={handleFileSelect}
+							disabled={testMode}
 						/>
 						<label htmlFor="tsv-file-upload">
 							<Button
@@ -122,6 +130,7 @@ const Pathways: React.FC = () => {
 								component="span"
 								startIcon={<CloudUpload />}
 								fullWidth
+								disabled={testMode}
 							>
 								{selectedFile ? selectedFile.name : "Choose TSV File"}
 							</Button>
@@ -137,21 +146,31 @@ const Pathways: React.FC = () => {
 					</Box>
 
 					<Box sx={{ flex: "1 1 300px", minWidth: 0 }}>
+						<FormControlLabel
+							control={
+								<Switch
+									checked={testMode}
+									onChange={(e) => setTestMode(e.target.checked)}
+								/>
+							}
+							label="Test Mode (Use Mock Data)"
+							sx={{ mb: 2 }}
+						/>
 						<Button
 							variant="contained"
 							color="primary"
 							onClick={handleSubmit}
-							disabled={!selectedFile || !library || loading}
+							disabled={(!selectedFile || !library) && !testMode || loading}
 							fullWidth
 							sx={{ mt: 4 }}
 						>
-							{loading ? "Running GSEA..." : "Run GSEA Analysis"}
+							{loading ? "Running GSEA..." : testMode ? "Show Test Data" : "Run GSEA Analysis"}
 						</Button>
 					</Box>
 				</Box>
 			</Box>
 
-			<PathwaysResults pathways={pathways} loading={loading} error={error} />
+			<PathwaysResults pathways={displayPathways} loading={displayLoading} error={displayError} />
 		</Container>
 	);
 };
diff --git a/uv.lock b/uv.lock
index 1f81303..d205c37 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,23 +1,29 @@
 version = 1
-revision = 2
 requires-python = ">=3.12"
 resolution-markers = [
-    "python_full_version >= '3.13'",
-    "python_full_version < '3.13'",
+    "python_full_version < '3.13' and sys_platform == 'win32'",
+    "python_full_version == '3.13.*' and sys_platform == 'win32'",
+    "python_full_version < '3.13' and sys_platform == 'emscripten'",
+    "python_full_version == '3.13.*' and sys_platform == 'emscripten'",
+    "python_full_version < '3.13' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version == '3.13.*' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
 ]
 
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265 },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.13.1"
+version = "3.13.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -28,76 +34,76 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ba/fa/3ae643cd525cf6844d3dc810481e5748107368eb49563c15a5fb9f680750/aiohttp-3.13.1.tar.gz", hash = "sha256:4b7ee9c355015813a6aa085170b96ec22315dabc3d866fd77d147927000e9464", size = 7835344, upload-time = "2025-10-17T14:03:29.337Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/1a/72/d463a10bf29871f6e3f63bcf3c91362dc4d72ed5917a8271f96672c415ad/aiohttp-3.13.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0760bd9a28efe188d77b7c3fe666e6ef74320d0f5b105f2e931c7a7e884c8230", size = 736218, upload-time = "2025-10-17T14:00:03.51Z" },
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 [[package]]
 name = "pathways-api"
 version = "0.1.0"
-source = { editable = "." }
+source = { virtual = "." }
 dependencies = [
     { name = "blitzgsea" },
     { name = "fastapi", extra = ["standard"] },
     { name = "gcsfs" },
     { name = "google-cloud-storage" },
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     { name = "pyspark" },
     { name = "python-dotenv" },
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-[package.dev-dependencies]
-dev = [
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-    { name = "pytest" },
-    { name = "pytest-asyncio" },
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+[package.dependency-groups]
 lint = [
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 ]
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 lint = [{ name = "ruff", specifier = ">=0.7.1" }]
 
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