from flask import (
Blueprint, request
)
from flask_restful_swagger_2 import Api, swagger, Resource
from ..util.utils import make_payload
from ..util.filter import parse_filter
class InitializeAPI(Resource):
@swagger.doc({
'summary': 'get metadata schema, ranges for values, and cell count to initialize cellxgene app',
'tags': ['initialize'],
'parameters': [],
'responses': {
'200': {
'description': 'initialization data for UI',
'examples': {
'application/json': {
"data": {
"cellcount": 3589,
"options": {
"Sample.type": {
"options": {
"Glioblastoma": 3589
}
},
"Selection": {
"options": {
"Astrocytes(HEPACAM)": 714,
"Endothelial(BSC)": 123,
"Microglia(CD45)": 1108,
"Neurons(Thy1)": 685,
"Oligodendrocytes(GC)": 294,
"Unpanned": 665
}
},
"Splice_sites_AT.AC": {
"range": {
"max": 1025,
"min": 152
}
},
"Splice_sites_Annotated": {
"range": {
"max": 1075869,
"min": 26
}
}
},
"schema": {
"CellName": {
"displayname": "Name",
"type": "string",
"variabletype": "categorical"
},
"Class": {
"displayname": "Class",
"type": "string",
"variabletype": "categorical"
},
"ERCC_reads": {
"displayname": "ERCC Reads",
"type": "int",
"variabletype": "continuous"
},
"ERCC_to_non_ERCC": {
"displayname": "ERCC:Non-ERCC",
"type": "float",
"variabletype": "continuous"
},
"Genes_detected": {
"displayname": "Genes Detected",
"type": "int",
"variabletype": "continuous"
}
},
"genes": ["1/2-SBSRNA4", "A1BG", "A1BG-AS1"]
},
"status": {
"error": False,
"errormessage": ""
}
}
}
}
}
})
def get(self):
from app import data, REACTIVE_LIMIT
return make_payload({
"schema": data.schema,
"cellcount": data.cell_count,
"reactivelimit": REACTIVE_LIMIT,
"genes": data.genes(),
"ranges": data.metadata_ranges(),
})
class CellsAPI(Resource):
@swagger.doc({
'summary': 'filter based on metadata fields to get a subset cells, expression data, and metadata',
'tags': ['cells'],
'description': "Cells takes query parameters defined in the schema retrieved from the /initialize enpoint. "
"
For categorical metadata keys filter based on `key=value`
"
" For continuous metadata keys filter by `key=min,max`
Either value "
"can be replaced by a \*. To have only a minimum value `key=min,\*` To have only a maximum "
"value `key=\*,max`
Graph data (if retrieved) is normalized"
" To only retrieve cells that don't have a value for the key filter by `key`",
'parameters': [],
'responses': {
'200': {
'description': 'initialization data for UI',
'examples': {
'application/json': {
"data": {
"badmetadatacount": 0,
"cellcount": 0,
"cellids": ["..."],
"metadata": [
{
"CellName": "1001000173.G8",
"Class": "Neoplastic",
"Cluster_2d": "11",
"Cluster_2d_color": "#8C564B",
"Cluster_CNV": "1",
"Cluster_CNV_color": "#1F77B4",
"ERCC_reads": "152104",
"ERCC_to_non_ERCC": "0.562454470489481",
"Genes_detected": "1962",
"Location": "Tumor",
"Location.color": "#FF7F0E",
"Multimapping_reads_percent": "2.67",
"Neoplastic": "Neoplastic",
"Non_ERCC_reads": "270429",
"Sample.name": "BT_S2",
"Sample.name.color": "#AEC7E8",
"Sample.type": "Glioblastoma",
"Sample.type.color": "#1F77B4",
"Selection": "Unpanned",
"Selection.color": "#98DF8A",
"Splice_sites_AT.AC": "102",
"Splice_sites_Annotated": "122397",
"Splice_sites_GC.AG": "761",
"Splice_sites_GT.AG": "125741",
"Splice_sites_non_canonical": "56",
"Splice_sites_total": "126660",
"Total_reads": "1741039",
"Unique_reads": "1400382",
"Unique_reads_percent": "80.43",
"Unmapped_mismatch": "2.15",
"Unmapped_other": "0.18",
"Unmapped_short": "14.56",
"housekeeping_cluster": "2",
"housekeeping_cluster_color": "#AEC7E8",
"recluster_myeloid": "NA",
"recluster_myeloid_color": "NA"
},
],
"reactive": True,
"graph": [
[
"1001000173.G8",
0.93836,
0.28623
],
[
"1001000173.D4",
0.1662,
0.79438
]
],
"status": {
"error": False,
"errormessage": ""
}
},
}
},
},
'400': {
'description': 'bad query params',
}
}
})
def get(self):
from app import data
payload = {
"cellids": [],
"metadata": [],
"cellcount": 0,
"graph": [],
"ranges": {},
}
# get query params
filter = parse_filter(request.args, data.schema)
filtered_data = data.filter_cells(filter)
payload["metadata"] = data.metadata(filtered_data)
payload["ranges"] = data.metadata_ranges(filtered_data)
payload["graph"] = data.create_graph(filtered_data)
payload["cellids"] = data.cellids(filtered_data)
payload["cellcount"] = len(payload["cellids"])
return make_payload(payload)
class ExpressionAPI(Resource):
@swagger.doc({
'summary': 'Json with gene list and expression data by cell, limited to first 40 cells',
'tags': ['expression'],
'parameters': [
{
'name': 'include_unexpressed_genes',
'description': "Include genes that have 0 expression across all cells in set",
'in': 'path',
'type': 'bool',
}
],
'responses': {
'200': {
'description': 'Json for heatmap',
'examples': {
'application/json': {
"data": {
"cells": [
{
"cellname": "1/2-SBSRNA4",
"e": [0, 0, 214, 0, 0]
},
],
"genes": [
"1001000173.G8",
"1001000173.D4",
"1001000173.B4",
"1001000173.A2",
"1001000173.E2"
],
"nonzero_gene_count": 2857
},
"status": {
"error": False,
"errormessage": ""
}
}
}
}
}
})
def get(self):
from app import data
expression_data = data.expression()
return make_payload(expression_data)
@swagger.doc({
'summary': 'Json with gene list and expression data by cell',
'tags': ['expression'],
'parameters': [
{
'name': 'body',
'in': 'body',
"schema": {
"example": {
"celllist": ["1001000173.G8", "1001000173.D4"],
"genelist": ["1/2-SBSRNA4", "A1BG", "A1BG-AS1", "A1CF", "A2LD1", "A2M", "A2ML1", "A2MP1",
"A4GALT"],
"include_unexpressed_genes": True,
}
}
},
],
'responses': {
'200': {
'description': 'Json for expressiondata',
'examples': {
'application/json': {
"data": {
"cells": [
{
"cellname": "1001000173.D4",
"e": [0, 0]
},
{
"cellname": "1001000173.G8",
"e": [0, 0]
}
],
"genes": [
"ABCD4",
"ZWINT"
],
"nonzero_gene_count": 2857
},
"status": {
"error": False,
"errormessage": ""
}
}
}
},
'400': {
'description': 'Required parameter missing/incorrect',
}
}
})
def post(self):
from app import data
args = request.get_json()
cell_list = args.get('celllist', [])
gene_list = args.get('genelist', [])
if not cell_list and not gene_list:
return make_payload([], "must include celllist and/or genelist parameter", 400)
expression_data = data.expression(cell_list, gene_list)
if cell_list and len(expression_data['cells']) < len(cell_list):
return make_payload([], "Some cell ids not available", 400)
if gene_list and len(expression_data['genes']) < len(gene_list):
return make_payload([], "Some genes not available", 400)
return make_payload(expression_data)
class DifferentialExpressionAPI(Resource):
@swagger.doc({
'summary': 'Get the top expressed genes for two cell sets. Calculated using t-test',
'tags': ['expression'],
'parameters': [
{
'name': 'body',
'in': 'body',
'schema': {
"example": {
"celllist1": ["1001000176.C12", "1001000176.C7", "1001000177.F11"],
"celllist2": ["1001000012.D2", "1001000017.F10", "1001000033.C3", "1001000229.D4"],
"num_genes": 5,
"pval": 0.000001,
},
}
}
],
"responses": {
'200': {
'description': 'top expressed genes for cellset1, cellset2',
'examples': {
'application/json': {
"data": {
"celllist1": {
"ave_diff": [
432.0132935431362,
12470.5623982637,
957.0246880086814
],
"mean_expression_cellset1": [
438.6185567010309,
13315.536082474227,
1076.5773195876288
],
"mean_expression_cellset2": [
6.605263157894737,
844.9736842105264,
119.55263157894737
],
"pval": [
3.8906598089944563e-35,
1.9086226376018916e-25,
7.847480544069826e-21
],
"topgenes": [
"TMSB10",
"FTL",
"TMSB4X"
]
},
"celllist2": {
"ave_diff": [
-6860.599158979924,
-519.1314432989691,
-10278.328269126423
],
"mean_expression_cellset1": [
2.8350515463917527,
0.6185567010309279,
23.09278350515464
],
"mean_expression_cellset2": [
6863.434210526316,
519.75,
10301.421052631578
],
"pval": [
4.662891833748732e-44,
3.6278087029927103e-37,
8.396825170618402e-35
],
"topgenes": [
"SPARCL1",
"C1orf61",
"CLU"
]
}
},
"status": {
"error": False,
"errormessage": ""
}
}
}
}
}
})
def post(self):
from app import data
args = request.get_json()
cell_list_1 = args.get('celllist1', [])
cell_list_2 = args.get('celllist2', [])
num_genes = args.get("num_genes", 7)
pval = args.get('pval', 0.5)
if not (cell_list_1 and cell_list_2):
return make_payload([],
"must include celllist1 and celllist2 parameters",
400)
data = data.diffexp(cell_list_1, cell_list_2, pval, num_genes)
return make_payload(data)
def get_api_resources():
bp = Blueprint('api', __name__, url_prefix='/api/v2.0')
api = Api(bp, add_api_spec_resource=False)
api.add_resource(InitializeAPI, "/initialize")
api.add_resource(CellsAPI, "/cells")
api.add_resource(ExpressionAPI, "/expression")
api.add_resource(DifferentialExpressionAPI, "/diffexp")
return api