Fix #86

Author: veghp

README.rst

@@ -64,7 +64,7 @@ The example below will generate a random sequence and optimize it so that:
             EnforceTranslation(location=(500, 1400))
         ],
         objectives=[CodonOptimize(species='e_coli', location=(500, 1400))]
-    )
+    )  # Note: always use a codon optimisation specification with EnforceTranslation
 
     # SOLVE THE CONSTRAINTS, OPTIMIZE WITH RESPECT TO THE OBJECTIVE
 

dnachisel/builtin_specifications/EnforceTranslation.py

@@ -20,6 +20,9 @@ class EnforceTranslation(CodonSpecification):
 
     Shorthand for annotations: "cds".
 
+    Note: always use a codon optimisation specification with EnforceTranslation.
+
+
     Parameters
     -----------
 
@@ -98,10 +101,7 @@ def set_location(self, location):
                 len(location) != 3 * len(self.translation)
             ):
                 raise ValueError(
-                    (
-                        "Window size (%d bp) incompatible with translation "
-                        "(%d aa)"
-                    )
+                    ("Window size (%d bp) incompatible with translation " "(%d aa)")
                     % (len(location), len(self.translation))
                 )
         self.location = location
@@ -119,10 +119,7 @@ def initialized_on_problem(self, problem, role):
             result = result.copy_with_changes(translation=translation)
         if len(result.location) != 3 * len(result.translation):
             raise ValueError(
-                (
-                    "Window size (%d bp) incompatible with translation "
-                    "(%d aa)"
-                )
+                ("Window size (%d bp) incompatible with translation " "(%d aa)")
                 % (len(result.location), len(result.translation))
             )
         if (result.start_codon is not None) and result.translation[0] != "M":
@@ -163,9 +160,11 @@ def evaluate(self, problem):
             problem,
             score=-len(errors_locations),
             locations=errors_locations,
-            message="All OK."
-            if len(errors_locations) == 0
-            else "Wrong translation at locations %s" % errors_locations,
+            message=(
+                "All OK."
+                if len(errors_locations) == 0
+                else "Wrong translation at locations %s" % errors_locations
+            ),
         )
 
     def localized_on_window(self, new_location, start_codon, end_codon):
@@ -179,7 +178,7 @@ def localized_on_window(self, new_location, start_codon, end_codon):
             translation=new_translation,
             boost=self.boost,
             genetic_table=self.genetic_table,
-            start_codon=self.start_codon if location_is_at_start else None
+            start_codon=self.start_codon if location_is_at_start else None,
             # has_start_codon=self.has_start_codon and location_is_at_start,
         )
 
@@ -196,11 +195,10 @@ def get_first_codon_choices(first_codon):
                 return [first_codon]
             else:
                 return [self.start_codon]  # "ATG"
+
         first_codon_location = self.codon_index_to_location(0)
         first_codon = first_codon_location.extract_sequence(sequence)
-        choices = [
-            (first_codon_location, get_first_codon_choices(first_codon))
-        ] + [
+        choices = [(first_codon_location, get_first_codon_choices(first_codon))] + [
             (self.codon_index_to_location(i), self.backtranslation_table[aa])
             for i, aa in list(enumerate(self.translation))[1:]
         ]
@@ -221,6 +219,6 @@ def __str__(self):
 
     def short_label(self):
         return "cds"
-    
+
     def breach_label(self):
         return "protein sequence changed"

dnachisel/builtin_specifications/codon_optimization/AvoidRareCodons.py

@@ -11,8 +11,8 @@ class AvoidRareCodons(BaseCodonOptimizationClass):
     This can be seen as a "mild" form of codon optimization where only rare
     codons (which slow down protein synthesis) are considered.
 
-    WARNING: Make sure to always use this specification with EnforceTranslation
-    to preserve the amino-acid sequence.
+    Warning: always use this specification with an EnforceTranslation constraint
+    defined over the same location, to preserve the amino acid sequence.
 
     Shorthand for annotations: "no_rare_codons".
 
@@ -25,7 +25,7 @@ class AvoidRareCodons(BaseCodonOptimizationClass):
       Name or TaxID of the species for which to optimize the sequence. A custom
       codon_usage_table can be provided instead (or in addition, for species
       names whose codon usage table cannot be imported).
-    
+
     codon_usage_table
       Optional codon usage table of the species for which the sequence will be
       codon-optimized, which can be provided instead of ``species``. A dict of
@@ -111,17 +111,17 @@ def evaluate(self, problem):
             problem,
             score=score,
             locations=locations,
-            message="All OK."
-            if len(locations) == 0
-            else "Rare codons at locations %s" % locations,
+            message=(
+                "All OK."
+                if len(locations) == 0
+                else "Rare codons at locations %s" % locations
+            ),
         )
 
     def restrict_nucleotides(self, sequence, location=None):
         nonrare_codons = list(self.nonrare_codons)
         if self.location.strand == -1:
-            nonrare_codons = sorted(
-                [reverse_complement(c) for c in nonrare_codons]
-            )
+            nonrare_codons = sorted([reverse_complement(c) for c in nonrare_codons])
         return [
             ((i, i + 3), nonrare_codons)
             for i in range(self.location.start, self.location.end, 3)

dnachisel/builtin_specifications/codon_optimization/CodonOptimize.py

@@ -10,7 +10,7 @@ def CodonOptimize(
     codon_usage_table=None,
     original_species=None,
     original_codon_usage_table=None,
-    boost=1.0
+    boost=1.0,
 ):
     """Codon-optimize a coding sequence using a user-selected method.
 
@@ -28,6 +28,10 @@ def CodonOptimize(
       codon whose usage in the target organism matches the usage of the
       original codon in its host organism (as per Claassens 2017).
 
+    Warning: always use this specification with an EnforceTranslation constraint
+    defined over the same location, to preserve the amino acid sequence.
+
+
     Parameters
     ==========
     species
@@ -105,5 +109,7 @@ def CodonOptimize(
             original_codon_usage_table=original_codon_usage_table,
             boost=boost,
         )
-    raise ValueError("`method` must be 'use_best_codon', 'match_codon_usage' "
-                     f"or 'harmonize_rca', not {method!r}")
+    raise ValueError(
+        "`method` must be 'use_best_codon', 'match_codon_usage' "
+        f"or 'harmonize_rca', not {method!r}"
+    )

dnachisel/builtin_specifications/codon_optimization/HarmonizeRCA.py

@@ -27,7 +27,8 @@ class HarmonizeRCA(BaseCodonOptimizationClass):
     algorithm (Angov 2008), which was much more complicated as it involved
     predicting "ribosome pausing" sites in the sequence.
 
-    Warning: always use with an EnforceTranslation constraint.
+    Warning: always use this specification with an EnforceTranslation constraint
+    defined over the same location, to preserve the amino acid sequence.
 
 
     Parameters

dnachisel/builtin_specifications/codon_optimization/MatchTargetCodonUsage.py

@@ -20,6 +20,10 @@ class MatchTargetCodonUsage(BaseCodonOptimizationClass):
     host-to-target codon harmonization. See DnaChisel's HarmonizeRCA class
     for Codon Harmonization.
 
+    Warning: always use this specification with an EnforceTranslation constraint
+    defined over the same location, to preserve the amino acid sequence.
+
+
     Parameters
     ----------
 
@@ -71,9 +75,7 @@ class MatchTargetCodonUsage(BaseCodonOptimizationClass):
 
     shorthand_name = "match_codon_usage"
 
-    def __init__(
-        self, species=None, location=None, codon_usage_table=None, boost=1.0
-    ):
+    def __init__(self, species=None, location=None, codon_usage_table=None, boost=1.0):
         BaseCodonOptimizationClass.__init__(
             self,
             species=species,
@@ -130,8 +132,7 @@ def evaluate(self, problem):
             problem,
             score=score,
             locations=locations,
-            message="Codon opt. on window %s scored %.02E"
-            % (self.location, score),
+            message="Codon opt. on window %s scored %.02E" % (self.location, score),
         )
 
     def localized_on_window(self, new_location, start_codon, end_codon):
@@ -177,9 +178,7 @@ def compare_frequencies(self, codons, text_mode=False):
         for i, codon in enumerate(codons):
             codons_positions[codon].append(i)
         # aa: amino-acid
-        codons_frequencies = {
-            aa: {"total": 0} for aa in self.codon_usage_table
-        }
+        codons_frequencies = {aa: {"total": 0} for aa in self.codon_usage_table}
         for codon, positions in codons_positions.items():
             count = len(positions)
             aa = self.codons_translations[codon]
@@ -191,9 +190,7 @@ def compare_frequencies(self, codons, text_mode=False):
                 if codon != "total":
                     data[codon] = 1.0 * value / total
         codons_frequencies = {
-            aa: data
-            for aa, data in codons_frequencies.items()
-            if data["total"]
+            aa: data for aa, data in codons_frequencies.items() if data["total"]
         }
         comparisons = {
             aa: {
@@ -209,8 +206,9 @@ def compare_frequencies(self, codons, text_mode=False):
             return dict_to_pretty_string(comparisons)
         else:
             return codons_positions, comparisons
+
     def short_label(self):
         result = "match-codon-usage"
         if self.species is not None:
             result += " (%s)" % self.species
-        return result
+        return result

dnachisel/builtin_specifications/codon_optimization/MaximizeCAI.py

@@ -20,6 +20,10 @@ class MaximizeCAI(BaseCodonOptimizationClass):
 
     This score is between -inf. and 0 (0 meaning a perfectly optimal sequence).
 
+    Warning: always use this specification with an EnforceTranslation constraint
+    defined over the same location, to preserve the amino acid sequence.
+
+
     Parameters
     ----------
 
@@ -65,9 +69,7 @@ class MaximizeCAI(BaseCodonOptimizationClass):
 
     shorthand_name = "use_best_codon"
 
-    def __init__(
-        self, species=None, location=None, codon_usage_table=None, boost=1.0
-    ):
+    def __init__(self, species=None, location=None, codon_usage_table=None, boost=1.0):
         BaseCodonOptimizationClass.__init__(
             self,
             species=species,
@@ -105,12 +107,10 @@ def evaluate(self, problem):
                 problem,
                 score=freq - optimal,
                 locations=[] if (freq == optimal) else [self.location],
-                message="Codon opt. on window %s scored %.02E"
-                % (self.location, score),
+                message="Codon opt. on window %s scored %.02E" % (self.location, score),
             )
         current_usage = [
-            self.codon_usage_table["log_codons_frequencies"][codon]
-            for codon in codons
+            self.codon_usage_table["log_codons_frequencies"][codon] for codon in codons
         ]
         optimal_usage = [
             self.codon_usage_table["log_best_frequencies"][ct[codon]]
@@ -125,8 +125,7 @@ def evaluate(self, problem):
             problem,
             score=score,
             locations=locations,
-            message="Codon opt. on window %s scored %.02E"
-            % (self.location, score),
+            message="Codon opt. on window %s scored %.02E" % (self.location, score),
         )
 
     def label_parameters(self):
@@ -137,4 +136,3 @@ def short_label(self):
         if self.species is not None:
             result += " (%s)" % self.species
         return result
-

dnachisel/builtin_specifications/codon_optimization/README.md

@@ -12,3 +12,6 @@ optimization that one can find in the literature.
 
 Finally, ``CodonOptimize`` is a generic pseudo-specification-class which uses a "mode"
 parameter to return a specification of one of the above classes.
+
+Warning: always use this specification with an EnforceTranslation constraint defined
+over the same location, to preserve the amino acid sequence.