mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-19 10:58:10 +08:00
85506db971
Fixes the build error in the old version. Reverted the API version since we changed directions from updating the API to refactoring the server structure instead.
442 lines
18 KiB
Python
442 lines
18 KiB
Python
from flask import (
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Blueprint, request
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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
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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 app import data, REACTIVE_LIMIT
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return make_payload({
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"schema": data.schema,
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"cellcount": data.cell_count,
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"reactivelimit": REACTIVE_LIMIT,
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"genes": data.genes(),
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"ranges": data.metadata_ranges(),
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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 app 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"] = data.metadata(filtered_data)
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payload["ranges"] = data.metadata_ranges(filtered_data)
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payload["graph"] = data.create_graph(filtered_data)
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payload["cellids"] = data.cellids(filtered_data)
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payload["cellcount"] = len(payload["cellids"])
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return make_payload(payload)
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class ExpressionAPI(Resource):
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@swagger.doc({
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"summary": "Json with gene list and expression data by cell, limited to first 40 cells",
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"tags": ["expression"],
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"parameters": [
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{
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"name": "include_unexpressed_genes",
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"description": "Include genes that have 0 expression across all cells in set",
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"in": "path",
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"type": "bool",
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}
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],
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"responses": {
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"200": {
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"description": "Json for heatmap",
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"examples": {
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"application/json": {
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"data": {
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"cells": [
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{
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"cellname": "1/2-SBSRNA4",
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"e": [0, 0, 214, 0, 0]
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},
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],
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"genes": [
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"1001000173.G8",
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"1001000173.D4",
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"1001000173.B4",
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"1001000173.A2",
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"1001000173.E2"
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],
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"nonzero_gene_count": 2857
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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 app import data
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expression_data = data.expression()
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return make_payload(expression_data)
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@swagger.doc({
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"summary": "Json with gene list and expression data by cell",
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"tags": ["expression"],
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"parameters": [
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{
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"name": "body",
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"in": "body",
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"schema": {
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"example": {
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"celllist": ["1001000173.G8", "1001000173.D4"],
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"genelist": ["1/2-SBSRNA4", "A1BG", "A1BG-AS1", "A1CF", "A2LD1", "A2M", "A2ML1", "A2MP1",
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"A4GALT"],
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"include_unexpressed_genes": True,
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}
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}
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},
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],
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"responses": {
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"200": {
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"description": "Json for expressiondata",
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"examples": {
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"application/json": {
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"data": {
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"cells": [
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{
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"cellname": "1001000173.D4",
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"e": [0, 0]
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},
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{
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"cellname": "1001000173.G8",
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"e": [0, 0]
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}
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],
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"genes": [
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"ABCD4",
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"ZWINT"
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],
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"nonzero_gene_count": 2857
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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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"400": {
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"description": "Required parameter missing/incorrect",
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}
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}
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})
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def post(self):
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from app import data
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args = request.get_json()
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cell_list = args.get("celllist", [])
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gene_list = args.get("genelist", [])
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if not cell_list and not gene_list:
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return make_payload([], "must include celllist and/or genelist parameter", 400)
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expression_data = data.expression(cell_list, gene_list)
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if cell_list and len(expression_data["cells"]) < len(cell_list):
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return make_payload([], "Some cell ids not available", 400)
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if gene_list and len(expression_data["genes"]) < len(gene_list):
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return make_payload([], "Some genes not available", 400)
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return make_payload(expression_data)
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class DifferentialExpressionAPI(Resource):
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@swagger.doc({
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"summary": "Get the top expressed genes for two cell sets. Calculated using t-test",
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"tags": ["expression"],
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"parameters": [
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{
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"name": "body",
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"in": "body",
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"schema": {
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"example": {
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"celllist1": ["1001000176.C12", "1001000176.C7", "1001000177.F11"],
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"celllist2": ["1001000012.D2", "1001000017.F10", "1001000033.C3", "1001000229.D4"],
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"num_genes": 5,
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"pval": 0.000001,
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},
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}
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}
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],
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"responses": {
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"200": {
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"description": "top expressed genes for cellset1, cellset2",
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"examples": {
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"application/json": {
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"data": {
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"celllist1": {
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"ave_diff": [
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432.0132935431362,
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12470.5623982637,
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957.0246880086814
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],
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"mean_expression_cellset1": [
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438.6185567010309,
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13315.536082474227,
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1076.5773195876288
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],
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"mean_expression_cellset2": [
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6.605263157894737,
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844.9736842105264,
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119.55263157894737
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],
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"pval": [
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3.8906598089944563e-35,
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1.9086226376018916e-25,
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7.847480544069826e-21
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],
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"topgenes": [
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"TMSB10",
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"FTL",
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"TMSB4X"
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]
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},
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"celllist2": {
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"ave_diff": [
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-6860.599158979924,
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-519.1314432989691,
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-10278.328269126423
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],
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"mean_expression_cellset1": [
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2.8350515463917527,
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0.6185567010309279,
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23.09278350515464
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],
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"mean_expression_cellset2": [
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6863.434210526316,
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519.75,
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10301.421052631578
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],
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"pval": [
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4.662891833748732e-44,
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3.6278087029927103e-37,
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8.396825170618402e-35
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],
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"topgenes": [
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"SPARCL1",
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"C1orf61",
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"CLU"
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]
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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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})
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def post(self):
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from app import data
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args = request.get_json()
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cell_list_1 = args.get("celllist1", [])
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cell_list_2 = args.get("celllist2", [])
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num_genes = args.get("num_genes", 7)
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pval = args.get("pval", 0.5)
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if not (cell_list_1 and cell_list_2):
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return make_payload([],
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"must include celllist1 and celllist2 parameters",
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400)
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data = data.diffexp(cell_list_1, cell_list_2, pval, num_genes)
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return make_payload(data)
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def get_api_resources():
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bp = Blueprint("api", __name__, url_prefix="/api/v0.1")
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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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api.add_resource(ExpressionAPI, "/expression")
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api.add_resource(DifferentialExpressionAPI, "/diffexp")
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return api
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