From 5a8d2b99b477e9063ff16b612e257e1b59456a91 Mon Sep 17 00:00:00 2001 From: Carlos Cruz Date: Tue, 21 Oct 2025 09:41:05 +0100 Subject: [PATCH 1/4] docker config --- Dockerfile | 15 ++++++++---- app/config.py | 9 ++++++- dev.sh | 57 +++++++++++++++++++++++++++++++++++++++++++++ docker-compose.yml | 10 ++++---- ui/.env.development | 2 ++ ui/.env.production | 1 + ui/index.html | 25 +++++++++++--------- ui/src/lib/api.ts | 12 +++++++++- 8 files changed, 110 insertions(+), 21 deletions(-) create mode 100644 dev.sh create mode 100644 ui/.env.development create mode 100644 ui/.env.production 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..11b9d53 100644 --- a/app/config.py +++ b/app/config.py @@ -15,15 +15,22 @@ class DevelopmentConfig(BaseConfig): "http://127.0.0.1:5173", # 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/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/ui/.env.development b/ui/.env.development new file mode 100644 index 0000000..5a8eb67 --- /dev/null +++ b/ui/.env.development @@ -0,0 +1,2 @@ +# Add a .env file for local development +VITE_API_URL=http://localhost:8080 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 @@ - - - - - Vite + React + TS - - -
- - - + + + + + + Vite + React + TS + + + +
+ + + + \ No newline at end of file diff --git a/ui/src/lib/api.ts b/ui/src/lib/api.ts index 8422402..179843d 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:8080'; +}; + +const API_BASE_URL = getApiBaseUrl(); export type Pathway = Record; From a495849147a83867a5f385bf06c9a3fe4aa69da3 Mon Sep 17 00:00:00 2001 From: Carlos Cruz Date: Wed, 29 Oct 2025 22:49:20 +0000 Subject: [PATCH 2/4] feat: create endpoint --- app/config.py | 8 +- app/routers/gsea.py | 71 +++- app/services/gsea.py | 43 +- ui/.env.development | 2 +- ui/package-lock.json | 395 +++++++++++++++++- ui/package.json | 2 + .../flame-graph/D3SunburstChart.tsx | 322 ++++++++++++++ .../flame-graph/PathwaysFlameGraph.tsx | 25 +- ui/src/components/flame-graph/index.ts | 1 + ui/src/data/mockPathwayData.ts | 123 ++++++ ui/src/lib/api.ts | 4 +- ui/src/pages/Pathways.tsx | 29 +- 12 files changed, 982 insertions(+), 43 deletions(-) create mode 100644 ui/src/components/flame-graph/D3SunburstChart.tsx create mode 100644 ui/src/data/mockPathwayData.ts diff --git a/app/config.py b/app/config.py index 11b9d53..3fd8866 100644 --- a/app/config.py +++ b/app/config.py @@ -12,7 +12,9 @@ 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 @@ -23,14 +25,16 @@ class DevelopmentConfig(BaseConfig): class ProductionConfig(BaseConfig): DEBUG = False # For Cloud Run, you need to add your actual domain - CORS_ORIGINS = os.getenv("CORS_ORIGINS", "").split(",") if os.getenv("CORS_ORIGINS") else ["*"] + 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/routers/gsea.py b/app/routers/gsea.py index 3121ff8..1f1bc69 100644 --- a/app/routers/gsea.py +++ b/app/routers/gsea.py @@ -1,4 +1,4 @@ -from fastapi import APIRouter, UploadFile, File, Query, HTTPException +from fastapi import APIRouter, UploadFile, File, Query, HTTPException, Body from app.services.gsea import run_gsea, available_gmt_files import tempfile import pandas as pd @@ -6,6 +6,7 @@ router = APIRouter() + @router.get("/gsea/libraries") async def list_gmt_files(): """List available GMT libraries.""" @@ -14,8 +15,11 @@ async def list_gmt_files(): @router.post("/gsea") async def gsea_endpoint( - 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)") + 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)"), ): # Validate file extension if not tsv_file.filename.endswith(".tsv"): @@ -30,8 +34,12 @@ async def gsea_endpoint( # 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).") + 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)}") @@ -44,3 +52,56 @@ async def gsea_endpoint( os.unlink(tsv_path) return res_df.to_dict(orient="records") + + +@router.post("/gsea/json") +async def gsea_json_endpoint( + gmt_name: str = Query(..., description="GMT library name (without .gmt extension)"), + payload: dict = Body( + ..., description="JSON body with 'genes': [{symbol, globalScore}]" + ), +): + """ + Run GSEA using JSON payload instead of file upload. + Expects: { "genes": [{"symbol": str, "globalScore": float}, ...] } + """ + # Validate payload + genes = payload.get("genes") if isinstance(payload, dict) else None + if not isinstance(genes, list) or len(genes) == 0: + raise HTTPException( + status_code=400, detail="Payload must include non-empty 'genes' list" + ) + + # Convert to DataFrame and validate columns + try: + df = pd.DataFrame(genes) + if not {"symbol", "globalScore"}.issubset(df.columns): + raise ValueError("Each gene must include 'symbol' and 'globalScore'") + except Exception as e: + raise HTTPException(status_code=400, detail=f"Invalid genes payload: {str(e)}") + + # Write to a temporary TSV and reuse existing analysis flow + with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".tsv") as tmp: + df.to_csv(tmp.name, sep="\t", index=False) + tsv_path = tmp.name + + try: + res_df = run_gsea(input_tsv=tsv_path, gmt_name=gmt_name) + except ValueError as e: + if "NaN" in str(e) or "nan" in str(e) or "solver cannot continue" in str(e): + raise 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: + raise HTTPException( + status_code=400, detail=f"GSEA analysis error: {str(e)}" + ) + except Exception as e: + raise HTTPException( + status_code=500, detail=f"Unexpected error during GSEA analysis: {str(e)}" + ) + finally: + os.unlink(tsv_path) + + return res_df.to_dict(orient="records") diff --git a/app/services/gsea.py b/app/services/gsea.py index b5711dd..3ce6600 100644 --- a/app/services/gsea.py +++ b/app/services/gsea.py @@ -7,14 +7,16 @@ DATA_DIR = BASE_DIR / "data" GMT_DIR = DATA_DIR / "gmt" + def load_custom_gmt(path): - with open(path, 'r') as f: + with open(path, "r") as f: return { parts[0]: parts[2:] for line in f - if (parts := line.strip().split('\t')) and len(parts) > 2 + if (parts := line.strip().split("\t")) and len(parts) > 2 } + def available_gmt_files(): """ Return available GMT libraries as: @@ -34,10 +36,11 @@ def available_gmt_files(): hierarchy_file = txt_files[0] if txt_files else None libraries[f"{folder.name}/{gmt_file.stem}"] = { "gmt": gmt_file, - "hierarchy": hierarchy_file + "hierarchy": hierarchy_file, } 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). @@ -58,7 +61,7 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4): # --- Check if GMT file contains IDs in braces {ID} --- contains_braces = False - with open(gmt_file, 'r') as f: + with open(gmt_file, "r") as f: for line in f: if "{" in line and "}" in line: contains_braces = True @@ -66,7 +69,7 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4): # Build ID -> genes mapping from the GMT file id_to_genes = {} - with open(gmt_file, 'r') as f: + with open(gmt_file, "r") as f: for line in f: parts = line.rstrip("\n").split("\t") if len(parts) > 2: @@ -100,7 +103,9 @@ 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 @@ -137,8 +142,10 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4): # --- Load hierarchy mapping if available --- if hierarchy_file and hierarchy_file.exists(): hierarchy_df = pd.read_csv( - hierarchy_file, sep="\t", header=None, - names=["Parent pathway", "Child pathway"] + hierarchy_file, + sep="\t", + header=None, + names=["Parent pathway", "Child pathway"], ) res_df = res_df.merge( hierarchy_df, left_on="ID", right_on="Child pathway", how="left" @@ -146,10 +153,19 @@ def run_gsea(input_tsv=None, gmt_name=None, processes=4): res_df = ( res_df.groupby( [ - "ID", "Link", "Pathway", "ES", "NES", "FDR", "p-value", - "Sidak's p-value", "Input gene number", "Leading edge genes", "Pathway size" + "ID", + "Link", + "Pathway", + "ES", + "NES", + "FDR", + "p-value", + "Sidak's p-value", + "Input gene number", + "Leading edge genes", + "Pathway size", ], - dropna=False + dropna=False, )["Parent pathway"] .apply(lambda x: ",".join(sorted(set(x.dropna())))) .reset_index() @@ -164,11 +180,10 @@ def safe_int_col(df_, col_name): """ if col_name in df_.columns: s = df_[col_name].astype(str).str.replace(",", "", regex=False).str.strip() - s = s.replace({'': None, 'nan': None}) - df_[col_name] = pd.to_numeric(s, errors='coerce').fillna(0).astype(int) + s = s.replace({"": None, "nan": None}) + df_[col_name] = pd.to_numeric(s, errors="coerce").fillna(0).astype(int) safe_int_col(res_df, "Input gene number") safe_int_col(res_df, "Pathway size") return res_df - diff --git a/ui/.env.development b/ui/.env.development index 5a8eb67..e8b2023 100644 --- a/ui/.env.development +++ b/ui/.env.development @@ -1,2 +1,2 @@ # Add a .env file for local development -VITE_API_URL=http://localhost:8080 +VITE_API_URL=http://localhost:8000 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 - 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"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 { + data: { + id: string; + name: string; + pathway?: Pathway; + pValue?: number; + fdr?: number; + nes?: number; + geneCount?: number; + genes?: string[]; + type: "root" | "pathway"; + }; +} + +const D3SunburstChart: React.FC = ({ + pathways, + maxPathways, + orientation, + branchvalues, +}) => { + const svgRef = useRef(null); + const containerRef = useRef(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): 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(); + 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},${height / 2})`); + + // Create partition layout + const partition = d3.partition() + .size([2 * Math.PI, radius]); + + // Create arc generator + const arc = d3.arc() + .startAngle(d => d.x0) + .endAngle(d => d.x1) + .padAngle(d => Math.min((d.x1 - d.x0) / 2, 0.005)) + .padRadius(radius / 2) + .innerRadius(d => d.y0) + .outerRadius(d => d.y1 - 1); + + // Create hierarchy + const root = d3.hierarchy(hierarchyData) + .sum(d => d.value) + .sort((a, b) => (b.value || 0) - (a.value || 0)); + + const nodes = partition(root).descendants().filter(d => d.x1 - d.x0 > 0.005); + + // Create arcs + const arcs = g + .selectAll(".arc") + .data(nodes) + .enter() + .append("path") + .attr("class", "arc") + .attr("d", arc) + .style("fill", d => d.data.color) + .style("cursor", "pointer") + .style("opacity", 0) + .on("mouseover", function(event, d) { + // Highlight current path + const sequenceArray = d.ancestors().reverse(); + + // Fade all arcs + arcs.transition().duration(300).style("opacity", 0.3); + + // Highlight current path + arcs + .filter(d => sequenceArray.indexOf(d) >= 0) + .transition() + .duration(300) + .style("opacity", 1); + + // Show tooltip (you can implement this based on your tooltip system) + showTooltip(event, d); + }) + .on("mouseleave", function() { + // Reset all arcs + arcs.transition().duration(300).style("opacity", 1); + hideTooltip(); + }) + .on("click", function(event, d) { + // Handle click events if needed + console.log("Clicked:", d.data); + }); + + // Animate arcs + arcs + .transition() + .delay((d, i) => i * 20) + .style("opacity", 1); + + // Add labels for larger arcs + const labels = g + .selectAll(".label") + .data(nodes.filter(d => d.x1 - d.x0 > 0.1 && d.y1 - d.y0 > 10)) + .enter() + .append("text") + .attr("class", "label") + .attr("transform", d => { + const x = (d.x0 + d.x1) / 2 * 180 / Math.PI; + const y = (d.y0 + d.y1) / 2; + return `rotate(${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 = ` +
${d.data.name}
+ ${d.data.type === "pathway" ? ` +
NES: ${d.data.nes?.toFixed(3) || "N/A"}
+
P-value: ${d.data.pValue?.toExponential(2) || "N/A"}
+
FDR: ${d.data.fdr?.toExponential(2) || "N/A"}
+
Genes: ${d.data.geneCount || 0}
+ ` : ""} + `; + + 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 ( + +
+ +
+ + ); +}; + +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 = ({ > } - label="Sunburst" + label="Plotly Sunburst" + iconPosition="start" + /> + } + label="D3 Sunburst" iconPosition="start" /> = ({ minHeight: "500px", }} > - {/* Sunburst Chart */} + {/* Plotly Sunburst Chart */} {activeTab === 0 && ( = ({ )} - {/* Horizontal Flame Graph Chart */} + {/* D3 Sunburst Chart */} {activeTab === 1 && ( + + + + )} + + {/* Horizontal Flame Graph Chart */} + {activeTab === 2 && ( { 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:8080'; + return import.meta.env.VITE_API_URL || 'http://localhost:8000'; }; const API_BASE_URL = getApiBaseUrl(); 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(null); const [library, setLibrary] = useState(""); const [fileError, setFileError] = useState(""); + const [testMode, setTestMode] = useState(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) => ( @@ -115,6 +122,7 @@ const Pathways: React.FC = () => { id="tsv-file-upload" type="file" onChange={handleFileSelect} + disabled={testMode} /> + setTestMode(e.target.checked)} + /> + } + label="Test Mode (Use Mock Data)" + sx={{ mb: 2 }} + /> - + ); }; From 0befaede40355060c95a1635d92c9ce643763cff Mon Sep 17 00:00:00 2001 From: Carlos Cruz Date: Thu, 30 Oct 2025 03:54:40 +0000 Subject: [PATCH 3/4] feat: clean up and migration --- app/controllers/hello.py | 0 app/main.py | 6 +- app/models/__init__.py | 3 + app/models/gsea.py | 24 +++++ app/routers/__init__.py | 6 ++ app/routers/gsea.py | 119 ++++++++++++------------ app/routers/pathways.py | 46 --------- app/routers/{umap_router.py => umap.py} | 0 app/services/__init__.py | 17 ++++ app/services/gsea.py | 61 +++++++++--- app/services/pathways_service.py | 41 -------- app/utils/__init__.py | 5 + app/utils/gsea_utils.py | 67 +++++++++++++ app/utils/spark.py | 15 --- app/utils/xml_parser.py | 11 --- ui/src/lib/api.ts | 4 +- 16 files changed, 232 insertions(+), 193 deletions(-) delete mode 100644 app/controllers/hello.py create mode 100644 app/models/gsea.py delete mode 100644 app/routers/pathways.py rename app/routers/{umap_router.py => umap.py} (100%) delete mode 100644 app/services/pathways_service.py create mode 100644 app/utils/gsea_utils.py delete mode 100644 app/utils/spark.py delete mode 100644 app/utils/xml_parser.py 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 9d0d9a6..57fcdc0 100644 --- a/app/main.py +++ b/app/main.py @@ -6,8 +6,7 @@ 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.umap import router as umap_router from app.routers import gsea import logging @@ -39,8 +38,7 @@ # Include routers app.include_router(gsea.router, prefix="/api", tags=["GSEA"]) -app.include_router(pathways_router) -app.include_router(router, prefix="/umap") +app.include_router(umap_router, prefix="/umap", tags=["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..22e383f 100644 --- a/app/routers/__init__.py +++ b/app/routers/__init__.py @@ -0,0 +1,6 @@ +"""API routers for the Pathways API.""" + +from app.routers import gsea +from app.routers import umap + +__all__ = ["gsea", "umap"] diff --git a/app/routers/gsea.py b/app/routers/gsea.py index 1f1bc69..526bc81 100644 --- a/app/routers/gsea.py +++ b/app/routers/gsea.py @@ -1,5 +1,7 @@ -from fastapi import APIRouter, UploadFile, File, Query, HTTPException, Body -from app.services.gsea import run_gsea, available_gmt_files +from fastapi import APIRouter, UploadFile, File, Query, HTTPException +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 @@ -13,95 +15,90 @@ async def list_gmt_files(): return list(available_gmt_files().keys()) -@router.post("/gsea") -async def gsea_endpoint( +@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)"), ): + """ + 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 = run_gsea(input_tsv=tsv_path, gmt_name=gmt_name) + # Run GSEA + res_df = 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) return res_df.to_dict(orient="records") -@router.post("/gsea/json") -async def gsea_json_endpoint( +@router.post("/gsea/analyze/json") +async def analyze_gsea_from_json( + request: GseaJsonRequest, gmt_name: str = Query(..., description="GMT library name (without .gmt extension)"), - payload: dict = Body( - ..., description="JSON body with 'genes': [{symbol, globalScore}]" - ), ): """ - Run GSEA using JSON payload instead of file upload. - Expects: { "genes": [{"symbol": str, "globalScore": float}, ...] } + 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} + ] + } """ - # Validate payload - genes = payload.get("genes") if isinstance(payload, dict) else None - if not isinstance(genes, list) or len(genes) == 0: - raise HTTPException( - status_code=400, detail="Payload must include non-empty 'genes' list" - ) - - # Convert to DataFrame and validate columns try: - df = pd.DataFrame(genes) - if not {"symbol", "globalScore"}.issubset(df.columns): - raise ValueError("Each gene must include 'symbol' and 'globalScore'") - except Exception as e: - raise HTTPException(status_code=400, detail=f"Invalid genes payload: {str(e)}") + # Convert request to DataFrame + genes_data = [ + {"symbol": g.symbol, "globalScore": g.globalScore} for g in request.genes + ] + df = pd.DataFrame(genes_data) - # Write to a temporary TSV and reuse existing analysis flow - with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".tsv") as tmp: - df.to_csv(tmp.name, sep="\t", index=False) - tsv_path = tmp.name + # Validate DataFrame (should already be valid via Pydantic, but double-check) + df = validate_gsea_dataframe(df) - try: - res_df = run_gsea(input_tsv=tsv_path, gmt_name=gmt_name) - except ValueError as e: - if "NaN" in str(e) or "nan" in str(e) or "solver cannot continue" in str(e): - raise 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: - raise HTTPException( - status_code=400, detail=f"GSEA analysis error: {str(e)}" - ) + # Run GSEA directly (no file I/O needed!) + res_df = run_gsea_from_dataframe(df, gmt_name) + + except HTTPException: + raise except Exception as e: - raise HTTPException( - status_code=500, detail=f"Unexpected error during GSEA analysis: {str(e)}" - ) - finally: - os.unlink(tsv_path) + raise handle_gsea_error(e) return res_df.to_dict(orient="records") diff --git a/app/routers/pathways.py b/app/routers/pathways.py deleted file mode 100644 index ced05b5..0000000 --- a/app/routers/pathways.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Any, Optional -from fastapi import APIRouter, HTTPException, Query, UploadFile, File, Form -import pandas as pd -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. - """ - try: - # Save uploaded file to a temporary path - tmp_path = Path(f"/tmp/{file.filename}") - with tmp_path.open("wb") as f: - f.write(await file.read()) - - res_df = 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)) diff --git a/app/routers/umap_router.py b/app/routers/umap.py similarity index 100% rename from app/routers/umap_router.py rename to app/routers/umap.py diff --git a/app/services/__init__.py b/app/services/__init__.py index e69de29..f0f012a 100644 --- a/app/services/__init__.py +++ b/app/services/__init__.py @@ -0,0 +1,17 @@ +"""Service layer for the Pathways API.""" + +from app.services.gsea import ( + available_gmt_files, + run_gsea, + run_gsea_from_dataframe, + load_custom_gmt, +) +from app.services.umap_service import perform_umap_clustering_api + +__all__ = [ + "available_gmt_files", + "run_gsea", + "run_gsea_from_dataframe", + "load_custom_gmt", + "perform_umap_clustering_api", +] diff --git a/app/services/gsea.py b/app/services/gsea.py index 3ce6600..e66aa63 100644 --- a/app/services/gsea.py +++ b/app/services/gsea.py @@ -41,14 +41,23 @@ 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 +) -> pd.DataFrame: """ - input_tsv = Path(input_tsv) if input_tsv else DEFAULT_TEST_INPUT + 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: + DataFrame with GSEA results + 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: raise ValueError(f"Invalid gmt_name. Choose from: {list(gmt_files.keys())}") @@ -85,14 +94,9 @@ 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") - - if set(df.columns) == set(range(len(df.columns))): - df = df.rename(columns={0: "symbol", 1: "globalScore"}) - + # Ensure DataFrame is properly formatted and sorted if not {"symbol", "globalScore"}.issubset(df.columns): - raise ValueError("Input file must contain 'symbol' and 'globalScore' columns.") + raise ValueError("DataFrame must contain 'symbol' and 'globalScore' columns.") df = df[["symbol", "globalScore"]].copy() df = df.sort_values("globalScore", ascending=False) @@ -187,3 +191,34 @@ def safe_int_col(df_, col_name): safe_int_col(res_df, "Pathway size") return res_df + + +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: + DataFrame with GSEA results + + 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/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/ui/src/lib/api.ts b/ui/src/lib/api.ts index b8e41ce..b46809f 100644 --- a/ui/src/lib/api.ts +++ b/ui/src/lib/api.ts @@ -75,12 +75,12 @@ class ApiClient { } } - // GSEA endpoint + // GSEA endpoint - file upload async runGsea(params: GseaParams): Promise> { const formData = new FormData(); formData.append('tsv_file', params.tsv_file); - return this.request(`/api/gsea?gmt_name=${encodeURIComponent(params.gmt_name)}`, { + return this.request(`/api/gsea/analyze/file?gmt_name=${encodeURIComponent(params.gmt_name)}`, { method: 'POST', body: formData, headers: {}, // Let the browser set the Content-Type for FormData From 5e6cce37c1448bbbfd3efd5e8a9232016b5aaac5 Mon Sep 17 00:00:00 2001 From: Carlos Cruz Date: Tue, 3 Feb 2026 01:11:57 +0000 Subject: [PATCH 4/4] refactor: update project metadata and dependencies - Updated project description for clarity. - Removed unnecessary classifiers and build-system configuration. - Added new dependency 'annotated-doc' and updated 'anyio' and 'certifi' versions. - Cleaned up imports in gsea.py by removing unused 'os' import. --- app/services/gsea.py | 1 - pyproject.toml | 40 +- uv.lock | 1479 +++++++++++++++++++++++------------------- 3 files changed, 802 insertions(+), 718 deletions(-) diff --git a/app/services/gsea.py b/app/services/gsea.py index e66aa63..2b92be9 100644 --- a/app/services/gsea.py +++ b/app/services/gsea.py @@ -1,4 +1,3 @@ -import os import pandas as pd import blitzgsea as blitz from pathlib import Path diff --git a/pyproject.toml b/pyproject.toml index f9231d1..9a80690 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, UMAP) 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 = [ @@ -26,29 +17,8 @@ dependencies = [ "pandas>=2.2.3", "umap>=0.1.1", "hdbscan>=0.8.40", - "numpy>=1.26.4" + "numpy>=1.26.4", ] -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["app"] - [dependency-groups] 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