fork/cellxgene
1
0
Fork 0
mirror of https://github.com/chanzuckerberg/cellxgene.git synced 2026-10-02 07:18:12 +08:00
Code Issues Packages Projects Releases Wiki Activity

Style guide cleanup

Browse Source
This commit is contained in:
Charlotte Weaver
2018-06-22 17:43:10 -07:00
parent 15ce4cc338
commit ca16447115
8 changed files with 930 additions and 45 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/app/scanpy_engine/scanpy_engine.py
+8 -19
View File
@@ -1,8 +1,9 @@
import scanpy.api as sc
import numpy as np
from scipy import stats
import os
import numpy as np
import scanpy.api as sc
from scipy import stats
from ..util.schema_parse import parse_schema
from ..driver.driver import CXGDriver
@@ -14,12 +15,10 @@ class ScanpyEngine(CXGDriver):
self.schema = self._load_or_infer_schema(data, schema)
self._set_cell_ids()
self.cell_count = self.data.shape[0]
# TODO Do I need this?
self.gene_count = self.data.shape[1]
self.graph_method = graph_method
self.diffexp_method = diffexp_method
@staticmethod
def _load_data(data):
return sc.read(os.path.join(data, "data.h5ad"))
@@ -30,7 +29,7 @@ class ScanpyEngine(CXGDriver):
if not schema:
pass
else:
data_schema = parse_schema(os.path.join(data,schema))
data_schema = parse_schema(os.path.join(data, schema))
return data_schema
def _set_cell_ids(self):
@@ -102,7 +101,6 @@ class ScanpyEngine(CXGDriver):
metadata[idx]["CellName"] = metadata[idx].pop("cell_name", None)
return metadata
def create_graph(self, df):
"""
Computes a n-d layout for cells through dimensionality reduction.
@@ -112,12 +110,11 @@ class ScanpyEngine(CXGDriver):
normalized_graph = (graph - graph.min()) / (graph.max() - graph.min())
return np.hstack((df.obs["cell_name"].values.reshape(len(df.obs.index), 1), normalized_graph)).tolist()
def diffexp(self, cell_list_1, cell_list_2, pval, num_genes):
cells_idx_1 = np.in1d(self.data.obs["cell_name"], cell_list_1)
cells_idx_2 = np.in1d(self.data.obs["cell_name"], cell_list_2)
expression_1 = self.data.X[cells_idx_1,:]
expression_2 = self.data.X[cells_idx_2,:]
expression_1 = self.data.X[cells_idx_1, :]
expression_2 = self.data.X[cells_idx_2, :]
diff_exp = stats.ttest_ind(expression_1, expression_2)
set1 = np.logical_and(diff_exp.pvalue < pval, diff_exp.statistic > 0)
set2 = np.logical_and(diff_exp.pvalue < pval, diff_exp.statistic < 0)
@@ -151,7 +148,7 @@ class ScanpyEngine(CXGDriver):
"ave_diff": mean_diff2.tolist()[:num_genes]
},
}
def expression(self, cells=None, genes=None):
"""
:param df:
@@ -185,11 +182,3 @@ class ScanpyEngine(CXGDriver):
"cells": cell_data,
"nonzero_gene_count": int(np.sum(expression.any(axis=0)))
}