mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-27 00:38:12 +08:00
Add backend to cellxgene repo
This commit is contained in:
Charlotte Weaver
+33
@@ -14,3 +14,36 @@ npm-debug.log
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.vscode
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data
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*.idea*
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__pycache__
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*.DS_Store*
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# Elastic Beanstalk Files
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.elasticbeanstalk/*
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!.elasticbeanstalk/*.cfg.yml
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!.elasticbeanstalk/*.global.yml
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GBM
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venv
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extesting
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Dockerfile-*
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*-data/*
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data/*
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runServer.py
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templates/favicon.png
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templates/index.html
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templates/service-worker.js
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templates/static/*
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Graph.dot*
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backend/app/web/static/css/
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backend/app/web/static/img/
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backend/app/web/static/js/
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backend/app/web/templates/index\.html
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@@ -1,9 +1 @@
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# cellxgene
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A React + Redux web application for exploring large scale single cell RNA sequence data.
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##### Quickstart:
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* `npm install`
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* `npm start`
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* `localhost:3000`
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cxg-v2
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@@ -0,0 +1,63 @@
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import os
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from flask import Flask, url_for, g
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from flask_compress import Compress
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from flask_cors import CORS
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from flask_restful_swagger_2 import get_swagger_blueprint
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# from werkzeug.contrib.profiler import ProfilerMiddleware
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from .web import webapp
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from .rest_api.rest import get_api_resources
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app = Flask(__name__)
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Compress(app)
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CORS(app)
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#Config
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CONFIG_FILE = os.environ.get("CXG_CONFIG_FILE", default="scanpy-test.cfg")
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CXG_DIR = os.environ.get("CXG_DIRECTORY", default="/Users/charlotteweaver/Documents/Git/cxg-v2/")
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SECRET_KEY = os.environ.get("CXG_SECRET_KEY", default="SparkleAndShine")
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# TODO remove the 2 when this is prod
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CXG_API_BASE = os.environ.get("CXG_API_BASE2", default="http://0.0.0.0:5005/api/")
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if not CONFIG_FILE:
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raise ValueError("No config file set for Flask application")
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app.config.from_pyfile(os.path.join(CXG_DIR, "config", CONFIG_FILE), silent=True)
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app.config.update(
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SECRET_KEY=SECRET_KEY,
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CXG_API_BASE=CXG_API_BASE,
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)
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app.config.update(
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DATA=os.path.join(CXG_DIR, app.config["DATA_DIR"]),
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)
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app.config['PROFILE'] = True
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# app.wsgi_app = ProfilerMiddleware(app.wsgi_app, restrictions=[15])
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# Application Data
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data = None
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if app.config["ENGINE"] == "scanpy":
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from .scanpy_engine.scanpy_engine import ScanpyEngine
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data = ScanpyEngine(app.config["DATA"])
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REACTIVE_LIMIT = 1_000_000
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# A list of swagger document objects
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docs = []
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resources = get_api_resources()
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docs.append(resources.get_swagger_doc())
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app.register_blueprint(webapp.bp)
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app.register_blueprint(resources.blueprint)
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app.register_blueprint(get_swagger_blueprint(docs, '/api/swagger', produces=["application/json"], title="cellxgene rest api",
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description='An API connecting ExpressionMatrix2 clustering algorithm to cellxgene'))
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app.add_url_rule('/', endpoint='index')
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if __name__ == "__main__":
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app.run(host='0.0.0.0', debug=True, port=5005)
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@@ -0,0 +1,57 @@
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from abc import ABC, abstractmethod
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class CXGDriver(metaclass=abc.ABCMeta):
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def __init__(self, data, schema=None, graph_method=None, diffexp_method=None):
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self.data = _load_data(data)
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@abstractmethod
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@staticmethod
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def _load_data(data):
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pass
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@abstractmethod
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def cells(self):
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pass
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@abstractmethod
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def cellids(self):
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pass
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@abstractmethod
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def genes(self):
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pass
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@abstractmethod
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def filter_cells(self, filter):
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"""
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Filter cells from data and return a subset of the data
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:param filter:
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:return: iterator through cells
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"""
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pass
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@abstractmethod
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def metadata_ranges(self, cells_iterator):
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"""
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"""
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pass
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@abstractmethod
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def metadata(self, cells_iterator):
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"""
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"""
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pass
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@abstractmethod
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def create_graph(self, cells_iterator):
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"""
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"""
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pass
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@abstractmethod
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def diffexp(self, cells_iterator):
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"""
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"""
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pass
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@@ -0,0 +1,215 @@
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from flask import (
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Blueprint, render_template, request, url_for
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)
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from flask_restful_swagger_2 import Api, swagger, Resource
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from ..util.utils import make_payload
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from ..util.filter import parse_filter, QueryStringError
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class InitializeAPI(Resource):
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@swagger.doc({
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'summary': 'get metadata schema, ranges for values, and cell count to initialize cellxgene app',
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'tags': ['initialize'],
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'parameters': [],
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'responses': {
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'200': {
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'description': 'initialization data for UI',
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'examples': {
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'application/json': {
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"data": {
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"cellcount": 3589,
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"options": {
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"Sample.type": {
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"options": {
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"Glioblastoma": 3589
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}
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},
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"Selection": {
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"options": {
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"Astrocytes(HEPACAM)": 714,
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"Endothelial(BSC)": 123,
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"Microglia(CD45)": 1108,
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"Neurons(Thy1)": 685,
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"Oligodendrocytes(GC)": 294,
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"Unpanned": 665
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}
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},
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"Splice_sites_AT.AC": {
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"range": {
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"max": 1025,
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"min": 152
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}
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},
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"Splice_sites_Annotated": {
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"range": {
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"max": 1075869,
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"min": 26
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}
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}
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},
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"schema": {
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"CellName": {
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"displayname": "Name",
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"type": "string",
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"variabletype": "categorical"
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},
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"Class": {
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"displayname": "Class",
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"type": "string",
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"variabletype": "categorical"
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},
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"ERCC_reads": {
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"displayname": "ERCC Reads",
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"type": "int",
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"variabletype": "continuous"
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},
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"ERCC_to_non_ERCC": {
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"displayname": "ERCC:Non-ERCC",
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"type": "float",
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"variabletype": "continuous"
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},
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"Genes_detected": {
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"displayname": "Genes Detected",
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"type": "int",
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"variabletype": "continuous"
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}
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},
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"genes": ["1/2-SBSRNA4", "A1BG", "A1BG-AS1"]
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},
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"status": {
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"error": False,
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"errormessage": ""
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}
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}
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}
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}
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}
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})
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def get(self):
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from cxg import data, REACTIVE_LIMIT
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return make_payload({
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"schema": data.schema,
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"ranges": data.metadata_ranges(data.ADATA, data.schema),
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"cellcount": data.cell_count(),
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"reactivelimit": REACTIVE_LIMIT,
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"genes": data.all_genes(),
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})
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class CellsAPI(Resource):
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@swagger.doc({
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'summary': 'filter based on metadata fields to get a subset cells, expression data, and metadata',
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'tags': ['cells'],
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'description': "Cells takes query parameters defined in the schema retrieved from the /initialize enpoint. "
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"<br>For categorical metadata keys filter based on `key=value` <br>"
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" For continuous metadata keys filter by `key=min,max`<br> Either value "
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"can be replaced by a \*. To have only a minimum value `key=min,\*` To have only a maximum "
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"value `key=\*,max` <br>Graph data (if retrieved) is normalized"
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" To only retrieve cells that don't have a value for the key filter by `key`",
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'parameters': [],
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'responses': {
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'200': {
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'description': 'initialization data for UI',
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'examples': {
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'application/json': {
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"data": {
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"badmetadatacount": 0,
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"cellcount": 0,
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"cellids": ["..."],
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"metadata": [
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{
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"CellName": "1001000173.G8",
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"Class": "Neoplastic",
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"Cluster_2d": "11",
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"Cluster_2d_color": "#8C564B",
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"Cluster_CNV": "1",
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"Cluster_CNV_color": "#1F77B4",
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"ERCC_reads": "152104",
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"ERCC_to_non_ERCC": "0.562454470489481",
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"Genes_detected": "1962",
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"Location": "Tumor",
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"Location.color": "#FF7F0E",
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"Multimapping_reads_percent": "2.67",
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"Neoplastic": "Neoplastic",
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"Non_ERCC_reads": "270429",
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"Sample.name": "BT_S2",
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"Sample.name.color": "#AEC7E8",
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"Sample.type": "Glioblastoma",
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"Sample.type.color": "#1F77B4",
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"Selection": "Unpanned",
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"Selection.color": "#98DF8A",
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"Splice_sites_AT.AC": "102",
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"Splice_sites_Annotated": "122397",
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"Splice_sites_GC.AG": "761",
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"Splice_sites_GT.AG": "125741",
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"Splice_sites_non_canonical": "56",
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"Splice_sites_total": "126660",
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"Total_reads": "1741039",
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"Unique_reads": "1400382",
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"Unique_reads_percent": "80.43",
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"Unmapped_mismatch": "2.15",
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"Unmapped_other": "0.18",
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"Unmapped_short": "14.56",
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"housekeeping_cluster": "2",
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"housekeeping_cluster_color": "#AEC7E8",
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"recluster_myeloid": "NA",
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"recluster_myeloid_color": "NA"
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},
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],
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"reactive": True,
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"graph": [
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[
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"1001000173.G8",
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0.93836,
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0.28623
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],
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[
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"1001000173.D4",
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0.1662,
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0.79438
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]
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],
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"status": {
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"error": False,
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"errormessage": ""
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}
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},
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}
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},
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},
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'400': {
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'description': 'bad query params',
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}
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}
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})
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def get(self):
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from cxg import data
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payload = {
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"cellids": [],
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"metadata": [],
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"cellcount": 0,
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"graph": [],
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"ranges": {},
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}
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# get query params
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filter = parse_filter(request.args, data.schema)
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filtered_data = data.filter_cells(filter)
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payload["metadata"], payload["cellids"] = data.metadata(filtered_data)
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payload["ranges"] = data.metadata_ranges(filtered_data, data.schema)
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payload["cellcount"] = len(payload["cellids"])
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payload["graph"] = data.create_graph(filtered_data)
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return make_payload(payload)
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def get_api_resources():
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bp = Blueprint('api', __name__, url_prefix='/api/v2.0')
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api = Api(bp, add_api_spec_resource=False)
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api.add_resource(InitializeAPI, "/initialize")
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api.add_resource(CellsAPI, "/cells")
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return api
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@@ -0,0 +1,86 @@
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from os.path import join
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import scanpy.api as sc
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import numpy as np
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from ..util.schema_parse import parse_schema
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class ScanpyEngine():
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def __init__(self, dataloc):
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self.ADATA = sc.read(join(dataloc, "data.h5ad"))
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self.cell_count = self._cell_count
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self.schema = parse_schema(join(dataloc, "data_schema.json"))
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def _cell_count(self):
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return len(self.ADATA.obs.index)
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def all_cells(self):
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return self.ADATA.obs.index.tolist()
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def all_genes(self):
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return self.ADATA.var.index.tolist()
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def gene_count(self):
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return len(self.ADATA.var.index)
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def filter_cells(self, filter):
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cell_idx = np.ones((self.cell_count(),), dtype=bool)
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for key, value in filter.items():
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if value["variable_type"] == "categorical":
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key_idx = np.in1d(getattr(self.ADATA.obs, key), value["query"])
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cell_idx = np.logical_and(cell_idx, key_idx)
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else:
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min_ = value["query"]["min"]
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max_ = value["query"]["max"]
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if min_:
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key_idx = np.array((getattr(self.ADATA.obs, key) >= min_).data)
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cell_idx = np.logical_and(cell_idx, key_idx)
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if max_:
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key_idx = np.array((getattr(self.ADATA.obs, key) <= min_).data)
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cell_idx = np.logical_and(cell_idx, key_idx)
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return self.ADATA[cell_idx, :]
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@staticmethod
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def metadata_ranges(data, schema):
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metadata_ranges = {}
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for field in schema:
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if schema[field]["variabletype"] == "categorical":
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group_by = field
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if group_by == "CellName":
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group_by = 'index'
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metadata_ranges[field] = {"options": data.obs.groupby(group_by).size().to_dict()}
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else:
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metadata_ranges[field] = {
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"range": {
|
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"min": data.obs[field].min(),
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||||
"max": data.obs[field].max()
|
||||
}
|
||||
}
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return metadata_ranges
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|
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@staticmethod
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def metadata(data):
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cell_ids = []
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metadata = data.obs.to_dict(orient="records")
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# Do i have to loop twice?
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for idx, cell_name in enumerate(data.obs.index):
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metadata[idx]["CellName"] = cell_name
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cell_ids.append(cell_name)
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return metadata, cell_ids
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|
||||
@staticmethod
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# TODO cache this
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# TODO accept n-dim versions too
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# TODO allow optional kw params to function
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def create_graph(data, graph_method="umap"):
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# Run the graph method
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getattr(sc.tl, graph_method)(data)
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graph = data.obsm["X_{graph_method}".format(graph_method=graph_method)]
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normalized_graph = (graph - graph.min()) / (graph.max() - graph.min())
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return np.hstack((data.obs.index.values.reshape(len(data.obs.index), 1), normalized_graph)).tolist()
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||||
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,62 @@
|
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class QueryStringError(Exception):
|
||||
pass
|
||||
|
||||
def _convert_variable(datatype, variable):
|
||||
"""
|
||||
Convert variable to number (float/int)
|
||||
Used for dataset metadata and for query string
|
||||
:param datatype: type to convert to
|
||||
:param variable: value of variable
|
||||
:return: converted variable
|
||||
:raises: ValueError
|
||||
"""
|
||||
try:
|
||||
if variable and datatype == "int":
|
||||
variable = int(variable)
|
||||
elif variable and datatype == "float":
|
||||
variable = float(variable)
|
||||
return variable
|
||||
except ValueError:
|
||||
raise
|
||||
|
||||
def parse_filter(filter, schema):
|
||||
"""
|
||||
{key: variable_type
|
||||
value_type
|
||||
query
|
||||
|
||||
:param filter:
|
||||
:param schema:
|
||||
:return:
|
||||
"""
|
||||
query = {}
|
||||
for key in filter:
|
||||
value = filter.getlist(key)
|
||||
if key not in schema:
|
||||
raise QueryStringError("Error: key {} not in metadata schema".format(key))
|
||||
query[key] = {
|
||||
"variable_type": schema[key]["variabletype"],
|
||||
"value_type": schema[key]["type"]
|
||||
}
|
||||
if query[key]["variable_type"] == "categorical":
|
||||
query[key]["query"] = _convert_variable(query[key]["value_type"], value)
|
||||
elif query[key]["variable_type"] == "continuous":
|
||||
value = value[0]
|
||||
try:
|
||||
min, max = value.split(",")
|
||||
except ValueError:
|
||||
raise QueryStringError("Error: min,max format required for range for key {}, got {}".format(key, value))
|
||||
if min == "*":
|
||||
min = None
|
||||
if max == "*":
|
||||
max = None
|
||||
try:
|
||||
query[key]["query"] = {
|
||||
"min": _convert_variable(query[key]["value_type"], min),
|
||||
"max": _convert_variable(query[key]["value_type"], max)
|
||||
}
|
||||
except ValueError:
|
||||
raise QueryStringError(
|
||||
"Error: expected type {} for key {}, got {}".format(query[key]["type"], key, value)
|
||||
)
|
||||
return query
|
||||
@@ -0,0 +1,7 @@
|
||||
import json
|
||||
|
||||
|
||||
def parse_schema(filename):
|
||||
with open(filename) as fh:
|
||||
schema = json.load(fh)
|
||||
return schema
|
||||
@@ -0,0 +1,34 @@
|
||||
import json
|
||||
from numpy import float32, integer
|
||||
from flask import make_response, jsonify
|
||||
|
||||
class Float32JSONEncoder(json.JSONEncoder):
|
||||
def default(self, obj):
|
||||
if isinstance(obj, float32):
|
||||
return float(obj)
|
||||
elif isinstance(obj, integer):
|
||||
return int(obj)
|
||||
return json.JSONEncoder.default(self, obj)
|
||||
|
||||
def make_payload(data, errormessage="", errorcode=200):
|
||||
"""
|
||||
Creates JSON respons for requests
|
||||
:param data: json data
|
||||
:param errormessage: error message
|
||||
:param errorcode: http error code
|
||||
:return: flask json repsonse
|
||||
"""
|
||||
error = False
|
||||
if errormessage:
|
||||
error = True
|
||||
# Questionable
|
||||
data = json.loads(json.dumps(data, cls=Float32JSONEncoder))
|
||||
return make_response(jsonify({
|
||||
"data": data,
|
||||
"status": {
|
||||
"error": error,
|
||||
"errormessage": errormessage,
|
||||
}
|
||||
}), errorcode)
|
||||
|
||||
|
||||
@@ -0,0 +1,97 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title>CellxGene REST API - Swagger definition</title>
|
||||
<link href="https://fonts.googleapis.com/css?family=Open+Sans:400,700|Source+Code+Pro:300,600|Titillium+Web:400,600,700"
|
||||
rel="stylesheet">
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/swagger-ui/3.2.1/swagger-ui.css"
|
||||
crossorigin="anonymous"/>
|
||||
<style>
|
||||
html {
|
||||
box-sizing: border-box;
|
||||
overflow: -moz-scrollbars-vertical;
|
||||
overflow-y: scroll;
|
||||
}
|
||||
|
||||
*,
|
||||
*:before,
|
||||
*:after {
|
||||
box-sizing: inherit;
|
||||
}
|
||||
|
||||
body {
|
||||
margin: 0;
|
||||
background: #fafafa;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
style="position:absolute;width:0;height:0">
|
||||
<defs>
|
||||
<symbol viewBox="0 0 20 20" id="unlocked">
|
||||
<path d="M15.8 8H14V5.6C14 2.703 12.665 1 10 1 7.334 1 6 2.703 6 5.6V6h2v-.801C8 3.754 8.797 3 10 3c1.203 0 2 .754 2 2.199V8H4c-.553 0-1 .646-1 1.199V17c0 .549.428 1.139.951 1.307l1.197.387C5.672 18.861 6.55 19 7.1 19h5.8c.549 0 1.428-.139 1.951-.307l1.196-.387c.524-.167.953-.757.953-1.306V9.199C17 8.646 16.352 8 15.8 8z"></path>
|
||||
</symbol>
|
||||
|
||||
<symbol viewBox="0 0 20 20" id="locked">
|
||||
<path d="M15.8 8H14V5.6C14 2.703 12.665 1 10 1 7.334 1 6 2.703 6 5.6V8H4c-.553 0-1 .646-1 1.199V17c0 .549.428 1.139.951 1.307l1.197.387C5.672 18.861 6.55 19 7.1 19h5.8c.549 0 1.428-.139 1.951-.307l1.196-.387c.524-.167.953-.757.953-1.306V9.199C17 8.646 16.352 8 15.8 8zM12 8H8V5.199C8 3.754 8.797 3 10 3c1.203 0 2 .754 2 2.199V8z"/>
|
||||
</symbol>
|
||||
|
||||
<symbol viewBox="0 0 20 20" id="close">
|
||||
<path d="M14.348 14.849c-.469.469-1.229.469-1.697 0L10 11.819l-2.651 3.029c-.469.469-1.229.469-1.697 0-.469-.469-.469-1.229 0-1.697l2.758-3.15-2.759-3.152c-.469-.469-.469-1.228 0-1.697.469-.469 1.228-.469 1.697 0L10 8.183l2.651-3.031c.469-.469 1.228-.469 1.697 0 .469.469.469 1.229 0 1.697l-2.758 3.152 2.758 3.15c.469.469.469 1.229 0 1.698z"/>
|
||||
</symbol>
|
||||
|
||||
<symbol viewBox="0 0 20 20" id="large-arrow">
|
||||
<path d="M13.25 10L6.109 2.58c-.268-.27-.268-.707 0-.979.268-.27.701-.27.969 0l7.83 7.908c.268.271.268.709 0 .979l-7.83 7.908c-.268.271-.701.27-.969 0-.268-.269-.268-.707 0-.979L13.25 10z"/>
|
||||
</symbol>
|
||||
|
||||
<symbol viewBox="0 0 20 20" id="large-arrow-down">
|
||||
<path d="M17.418 6.109c.272-.268.709-.268.979 0s.271.701 0 .969l-7.908 7.83c-.27.268-.707.268-.979 0l-7.908-7.83c-.27-.268-.27-.701 0-.969.271-.268.709-.268.979 0L10 13.25l7.418-7.141z"/>
|
||||
</symbol>
|
||||
|
||||
|
||||
<symbol viewBox="0 0 24 24" id="jump-to">
|
||||
<path d="M19 7v4H5.83l3.58-3.59L8 6l-6 6 6 6 1.41-1.41L5.83 13H21V7z"/>
|
||||
</symbol>
|
||||
|
||||
<symbol viewBox="0 0 24 24" id="expand">
|
||||
<path d="M10 18h4v-2h-4v2zM3 6v2h18V6H3zm3 7h12v-2H6v2z"/>
|
||||
</symbol>
|
||||
|
||||
</defs>
|
||||
</svg>
|
||||
|
||||
<div id="swagger-ui"></div>
|
||||
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/swagger-ui/3.2.1/swagger-ui-bundle.js"
|
||||
crossorigin="anonymous"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/swagger-ui/3.2.1/swagger-ui-standalone-preset.js"
|
||||
crossorigin="anonymous"></script>
|
||||
<script>
|
||||
window.onload = function () {
|
||||
const ui = SwaggerUIBundle({
|
||||
url: window.location.origin + "/api/swagger.json",
|
||||
dom_id: '#swagger-ui',
|
||||
deepLinking: true,
|
||||
presets: [
|
||||
SwaggerUIBundle.presets.apis,
|
||||
SwaggerUIStandalonePreset
|
||||
],
|
||||
plugins: [
|
||||
SwaggerUIBundle.plugins.DownloadUrl
|
||||
],
|
||||
layout: "StandaloneLayout"
|
||||
});
|
||||
|
||||
window.ui = ui
|
||||
}
|
||||
</script>
|
||||
</body>
|
||||
|
||||
</html>
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,22 @@
|
||||
from flask import (
|
||||
Blueprint, render_template, request, url_for, current_app
|
||||
)
|
||||
|
||||
bp = Blueprint('webapp', __name__, template_folder='templates')
|
||||
|
||||
@bp.route('/')
|
||||
def index():
|
||||
url_base = current_app.config["CXG_API_BASE"]
|
||||
dataset_title = current_app.config["DATASET_TITLE"]
|
||||
return render_template("index.html", prefix=url_base, datasetTitle=dataset_title)
|
||||
|
||||
|
||||
# renders swagger documentation
|
||||
@bp.route('/swagger')
|
||||
def swag():
|
||||
return render_template("swagger.html")
|
||||
|
||||
# renders swagger documentation
|
||||
@bp.route('/favicon.png')
|
||||
def favicon():
|
||||
return url_for("static", filename="img/favicon.png")
|
||||
@@ -0,0 +1,3 @@
|
||||
from cxg import app
|
||||
|
||||
app.run(host='0.0.0.0', debug=True, port=5005)
|
||||
File diff suppressed because one or more lines are too long
|
Before Width: | Height: | Size: 43 KiB After Width: | Height: | Size: 43 KiB |
Reference in New Issue
Block a user