Merge branch 'develop' into master

gimmemotifs/c_metrics.c

@@ -211,6 +211,7 @@ double matrix_ed_mean(double matrix1[][4], double matrix2[][4], int length) {
 
 double distance(double col1[], double col2[]) {
 	// Return the distance between two motifs (Harbison et al.) 
+	// https://www.nature.com/articles/nature02800#Sec2
 	int n;
 	double d = 0;
 

gimmemotifs/commands/motifs.py

@@ -14,6 +14,7 @@
 
 import numpy as np
 import pandas as pd
+from tqdm.auto import tqdm
 
 from gimmemotifs.background import create_background_file
 from gimmemotifs.comparison import MotifComparer, select_nonredundant_motifs
@@ -255,7 +256,8 @@ def motifs(args):
     # At the moment this is not ideal, as scanning is now performed twice
     # for this set of non-redundant motifs.
     motif_dict = dict([(m.id, m) for m in motifs])
-    for motif in nr_motifs:
+    logger.info("creating BED files with scan results")
+    for motif in tqdm(nr_motifs):
         with NamedTemporaryFile(mode="w") as f:
             print(motif_dict[motif].to_ppm(), file=f)
             f.flush()
@@ -270,6 +272,7 @@ def motifs(args):
                 zscore=args.zscore,
                 gcnorm=args.gc,
                 bgfile=bgfile,
+                progress=False,
             )
 
     if args.report:

gimmemotifs/comparison.py

@@ -26,7 +26,7 @@
 from gimmemotifs.config import MotifConfig
 from gimmemotifs.c_metrics import pfmscan, score
 from gimmemotifs.motif import parse_motifs, read_motifs
-from gimmemotifs.utils import pfmfile_location, make_equal_length
+from gimmemotifs.utils import pfmfile_location, make_equal_length, ppm_pseudocount
 
 # pool import is at the bottom
 
@@ -204,6 +204,7 @@ def chisq(p1, p2):
     -------
     score : float
     """
+
     return chi2_contingency([p1, p2])[1]
 
 
@@ -440,8 +441,13 @@ def compare_motifs(
                         combine,
                         self.max_partial(m1.pwm, m2.pwm, metric, combine),
                     )
-                elif metric in ["pcc", "ed", "distance", "wic", "chisq", "ssd"]:
-                    return self.max_partial(m1.pwm, m2.pwm, metric, combine)
+                elif metric in ["pcc", "ed", "distance", "wic", "chisq", "ssd", "akl"]:
+                    return self.max_partial(
+                        ppm_pseudocount(m1.pwm),
+                        ppm_pseudocount(m2.pwm),
+                        metric,
+                        combine,
+                    )
                 else:
                     return self.max_partial(m1.pfm, m2.pfm, metric, combine)
 
@@ -455,19 +461,33 @@ def compare_motifs(
                         combine,
                         self.max_total(m1.pwm, m2.pwm, metric, combine),
                     )
-                elif metric in ["pcc", "akl"]:
-                    # Slightly randomize the weight matrix
+                elif metric in [
+                    "ed",
+                    "distance",
+                    "wic",
+                    "chisq",
+                    "pcc",
+                    "ssd",
+                    "akl",
+                    "pcc",
+                ]:
                     return self.max_total(
-                        m1.wiggle_pwm(), m2.wiggle_pwm(), metric, combine
+                        ppm_pseudocount(m1.pwm),
+                        ppm_pseudocount(m2.pwm),
+                        metric,
+                        combine,
                     )
-                elif metric in ["ed", "distance", "wic", "chisq", "pcc", "ssd"]:
-                    return self.max_total(m1.pwm, m2.pwm, metric, combine)
                 else:
                     return self.max_total(m1.pfm, m2.pfm, metric, combine)
 
             elif match == "subtotal":
                 if metric in ["pcc", "ed", "distance", "wic", "chisq", "ssd"]:
-                    return self.max_subtotal(m1.pwm, m2.pwm, metric, combine)
+                    return self.max_subtotal(
+                        ppm_pseudocount(m1.pwm),
+                        ppm_pseudocount(m2.pwm),
+                        metric,
+                        combine,
+                    )
                 else:
                     return self.max_subtotal(m1.pfm, m2.pfm, metric, combine)
         else:

gimmemotifs/moap.py

@@ -691,7 +691,7 @@ def moap(
         motif_names = [m.id for m in read_motifs(pfmfile)]
         scores = []
         if method == "classic" or scoring == "count":
-            logger.info("motif scanning (scores)")
+            logger.info("motif scanning (counts)")
             scores = scan_regionfile_to_table(
                 inputfile,
                 genome,

gimmemotifs/motif/__init__.py

@@ -97,7 +97,7 @@ def __init__(self, pfm=None, ppm=None, places=4):
             else:
                 self.pfm = []
         else:
-            if np.all(np.isclose(np.sum(pfm, 1), 1)) and ppm is None:
+            if np.all(np.isclose(np.sum(pfm, 1), 1, atol=1e-3)) and ppm is None:
                 # PFM is specified actually a PPM. We don't mind.
                 self.ppm = pfm
             else:

gimmemotifs/motif/_comparison.py

@@ -54,7 +54,14 @@ def pcc(self, ppm1, ppm2, pos):
     ppm1, ppm2 = make_equal_length(ppm1, ppm2, pos, truncate="both")
 
     # Compute pearson correlation between aligned parts of the motif
-    r = np.array([pearsonr(x, y)[0] for x, y in zip(ppm1, ppm2)])
+    r = np.array(
+        [
+            pearsonr(x, y)[0]
+            if not (np.all(x == 0.25)) or not (np.all(y == 0.25))
+            else 0
+            for x, y in zip(ppm1, ppm2)
+        ]
+    )
     r[np.isnan(r)] = 0
 
     return r.sum()

gimmemotifs/orthologs.py

@@ -431,6 +431,7 @@ def load_orthogroups_in_db(db, genomes, orthofinder_result):
             for gene in genes.split(", "):
                 # for each gene we store its gene_name (if present,
                 # otherwise .) and gene_id. We load them both in the database.
+                gene = gene.replace("'", "")
                 gene_name, gene_id = gene.split("|")
                 if gene_name != ".":
                     conn.execute(
@@ -449,6 +450,7 @@ def load_orthogroups_in_db(db, genomes, orthofinder_result):
 
             # for each gene we store its gene_name (if present,
             # otherwise .) and gene_id. We load them both in the database.
+            gene = gene.replace("'", "")
             gene_name, gene_id = gene.split("|")
             if gene_name != ".":
                 conn.execute(

gimmemotifs/report.py

@@ -141,9 +141,9 @@ def _current_index(self, subset):
         ]
         return idx_slice
 
-    def _translate(self):
+    def _translate(self, *args, **kwargs):
         self._compute_data()
-        d = super()._translate()
+        d = super()._translate(*args, **kwargs)
         circle_styles = self.circle_styles or []
         palette_styles = self.palette_styles or []
         col_heading_style = self.col_heading_style or []