Merge pull request #152 from Genentech/tangermeme-update

Tangermeme update

Author: avantikalal

setup.cfg

@@ -70,7 +70,8 @@ install_requires =
     logomaker >= 0.8
     pyBigWig
     ledidi < 2.0.0
-    tangermeme >= 0.4.0,< 0.5.0
+    tangermeme >= 0.5.0
+    memelite
     pygenomeviz <= 0.4.4
     statsmodels >=0.11.1
     pyjaspar >=3.0

src/grelu/interpret/motifs.py

@@ -122,8 +122,7 @@ def scan_sequences(
     attrs: Optional[np.ndarray] = None,
 ):
     """
-    Scan a DNA sequence using motifs. Based on
-    https://github.com/jmschrei/tangermeme/blob/main/tangermeme/tools/fimo.py.
+    Scan a DNA sequence using motifs. Based on https://github.com/jmschrei/memesuite-lite.
 
     Args:
         seqs: A string or a list of DNA sequences as strings
@@ -148,7 +147,7 @@ def scan_sequences(
         pd.DataFrame containing columns 'motif', 'sequence', 'start', 'end',
         'strand', 'score', 'pval', and 'matched_seq'.
     """
-    from tangermeme.tools.fimo import fimo
+    from memelite import fimo
 
     # Format sequences
     seqs = make_list(seqs)
@@ -369,7 +368,7 @@ def compare_motifs(
 def run_tomtom(motifs: Dict[str, np.ndarray], meme_file: str) -> pd.DataFrame:
     """
     Function to compare given motifs to reference motifs using the
-    tomtom algorithm, as implemented in tangermeme.
+    tomtom algorithm, as implemented in memelite (https://github.com/jmschrei/memesuite-lite).
 
     Args:
         motifs: A dictionary whose values are Position Probability Matrices
@@ -380,7 +379,7 @@ def run_tomtom(motifs: Dict[str, np.ndarray], meme_file: str) -> pd.DataFrame:
         df: Pandas dataframe containing all tomtom results.
     """
     from statsmodels.stats.multitest import fdrcorrection
-    from tangermeme.tools.tomtom import tomtom
+    from memelite import tomtom
 
     from grelu.interpret.motifs import motifs_to_strings
     from grelu.resources import get_meme_file_path

src/grelu/io/motifs.py

@@ -27,7 +27,7 @@ def read_meme_file(
         values are the motif position probability matrices (PPMs)
         as numpy arrays of shape (4, L).
     """
-    from tangermeme.io import read_meme
+    from memelite.io import read_meme
 
     from grelu.resources import get_meme_file_path
 
@@ -48,9 +48,6 @@ def read_meme_file(
 
         motifs = motifs_subset
 
-    # Convert to numpy
-    motifs = {k: v.numpy() for k, v in motifs.items()}
-
     return motifs