Merge pull request #63 from dpeerlab/fix_hvg

Fix args to highly_variable_genes function in ENVI.py
dpeerlab · May 20, 2024 · 908b12b · 908b12b
2 parents 0f145a1 + 3923485
commit 908b12b
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Showing 3 changed files with 23 additions and 13 deletions.
diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "scenvi"
-version = "0.3.3"
+version = "0.3.4"
 description = "Integration of scRNA-seq and spatial transcriptomics data"
 authors = ["Doron Haviv"]
 license = "MIT"

diff --git a/scenvi/ENVI.py b/scenvi/ENVI.py
@@ -77,18 +77,22 @@ def __init__(
         stable_eps=1e-6,
     ):
 
-        self.spatial_data = spatial_data
+        self.spatial_data = spatial_data[:, np.intersect1d(spatial_data.var_names, sc_data.var_names)]
         self.sc_data = sc_data
 
-        if "highly_variable" not in sc_data.var.columns:
-
-            sc_data.layers["log"] = np.log(sc_data.X + 1)
-            sc.pp.highly_variable_genes(
-                sc_data, layer="log", n_top_genes=min(num_HVG, sc_data.shape[-1])
-            )
+        if "highly_variable" not in self.sc_data.var.columns:
+            if 'log' in self.sc_data.layers.keys():
+                sc.pp.highly_variable_genes(self.sc_data, n_top_genes=num_HVG, layer="log")
+            elif('log1p' in self.sc_data.layers.keys()):
+                sc.pp.highly_variable_genes(self.sc_data, n_top_genes=num_HVG, layer="log1p")
+            elif(self.sc_data.X.min() < 0):
+                sc.pp.highly_variable_genes(self.sc_data, n_top_genes=num_HVG)
+            else:
+                sc_data.layers["log"] = np.log(self.sc_data.X + 1)
+                sc.pp.highly_variable_genes(self.sc_data, n_top_genes=num_HVG, layer="log")
 
         sc_genes_keep = np.union1d(
-            sc_data.var_names[sc_data.var.highly_variable], self.spatial_data.var_names
+            self.sc_data.var_names[self.sc_data.var.highly_variable], self.spatial_data.var_names
         )
         if len(sc_genes) > 0:
             sc_genes_keep = np.union1d(sc_genes_keep, sc_genes)

diff --git a/scenvi/utils.py b/scenvi/utils.py
@@ -9,7 +9,7 @@
 from flax import struct
 from flax.training import train_state
 from jax import random
-
+import scipy.sparse
 
 class FeedForward(nn.Module):
     """
@@ -254,7 +254,6 @@ def niche_cell_type(
     )
     return cell_type_niche
 
-
 def compute_covet(
     spatial_data, k=8, g=64, genes=[], spatial_key="spatial", batch_key=-1
 ):
@@ -277,8 +276,15 @@ def compute_covet(
         CovGenes = spatial_data.var_names
     else:
         if "highly_variable" not in spatial_data.var.columns:
-            spatial_data.layers["log"] = np.log(spatial_data.X + 1)
-            sc.pp.highly_variable_genes(spatial_data, n_top_genes=g, layer="log")
+            if 'log' in spatial_data.layers.keys():
+                sc.pp.highly_variable_genes(spatial_data, n_top_genes=g, layer="log")
+            elif('log1p' in spatial_data.layers.keys()):
+                sc.pp.highly_variable_genes(spatial_data, n_top_genes=g, layer="log1p")
+            elif(spatial_data.X.min() < 0):
+                sc.pp.highly_variable_genes(spatial_data, n_top_genes=g)
+            else:
+                spatial_data.layers["log"] = np.log(spatial_data.X + 1)
+                sc.pp.highly_variable_genes(spatial_data, n_top_genes=g, layer="log")
 
         CovGenes = np.asarray(spatial_data.var_names[spatial_data.var.highly_variable])
         if len(genes) > 0: