Fix melting functions and add shift_melt_cutsite_pairs

pyproject.toml

@@ -38,7 +38,7 @@ repository = "https://github.com/pydna-group/pydna/tree/master"
 version = "6.0.0-a.24.post.17+b7b559bd66"
 [tool.poetry.dependencies]
 appdirs = ">=1.4.4"
-biopython = "1.85"
+biopython = "^1.86"
 cai2 = { version = ">=1.0.5", optional = true }
 matplotlib = { version = ">=3.4.3", optional = true }
 networkx = ">=2.8.8"

src/pydna/alphabet.py

@@ -887,7 +887,7 @@ def regex_ss_melt_factory(length: int) -> re.Pattern:
     return re.compile(regex.encode("ascii"))
 
 
-def regex_ds_melt_factory(length: int) -> re.Pattern:
+def regex_ds_melt_factory(length: int, circular: bool) -> re.Pattern:
     """
     A regular expression for finding double-stranded regions flanked by single-stranded DNA
     that can be melted to shed multiple double stranded fragments.
@@ -907,11 +907,35 @@ def regex_ds_melt_factory(length: int) -> re.Pattern:
         aaaG TTACAttt   <-- "TTA" is found by the regex for length <= 3
         tttCTAAT Taaa
 
+    The name of the capture groups (watson and crick) identifies the ssDNA
+    strand on the left side of the dsDNA. For example:
+
+    ::
+        gCtC  CTTCtC  CTg
+         GaGAAGAAGaGAAGA
+
+    The first capture group CtC starts with ssDNA on the watson strand,
+    then dsDNA, then ssNDA on the crick strand and the match will be
+    ``{'watson': b'CtC', 'crick': None}``.
+
+    The second capture group CTg starts with ssDNA on the crick strand,
+    then dsDNA, then ssNDA on the watson strand and the match will be
+    ``{'watson': None, 'crick': b'CTg'}``.
+
+    This can be slightly confusing if there are no overhangs, for example:
+
+    ::
+        CtC  CTTCtC  CT
+        GaGAAGAAGaGAAGA
+
+    Will give ``{'watson': b'CtC', 'crick': None}``, because it "could have
+    started" with the ssDNA on the watson strand, but not on the crick strand.
+
     Examples
     --------
 
     >>> from pydna.dseq import Dseq
-    >>> regex = regex_ds_melt_factory(3)
+    >>> regex = regex_ds_melt_factory(3, False)
     >>> s = Dseq("aaaGFTTAIAttt")
     >>> s
     Dseq(-13)
@@ -926,21 +950,26 @@ def regex_ds_melt_factory(length: int) -> re.Pattern:
     length : int
         Max length of double stranded region flanked by single stranded
         regions.
+    circular : bool
+        Whether the sequence is circular.
 
     Returns
     -------
-    TYPE
+    re.Pattern
         regular expression object.
 
     """
 
+    start_if_not_circular = "|^" if not circular else ""
+    end_if_not_circular = "|$" if not circular else ""
+
     regex = (
-        f"(?P<watson>((?<=[{ss_letters_watson}])|^)"
+        f"(?P<watson>((?<=[{ss_letters_watson}]){start_if_not_circular})"
         f"([{ds_letters}]{{1,{length}}})"
-        f"((?=[^{ss_letters_watson}{ds_letters}])|$))|"
-        f"(?P<crick>((?<=[{ss_letters_crick}])|^)"
+        f"((?=[{ss_letters_crick}]){end_if_not_circular}))|"
+        f"(?P<crick>((?<=[{ss_letters_crick}]){start_if_not_circular})"
         f"([{ds_letters}]{{1,{length}}})"
-        f"((?=[^{ss_letters_crick}{ds_letters}])|$))"
+        f"((?=[{ss_letters_watson}]){end_if_not_circular}))"
     )
 
     return re.compile(regex.encode("ascii"))

src/pydna/cre_lox.py

@@ -5,7 +5,7 @@
 from Bio.Seq import reverse_complement
 from pydna.sequence_regex import compute_regex_site, dseqrecord_finditer
 from Bio.SeqFeature import Location, SimpleLocation, SeqFeature
-from pydna.utils import shift_location
+from pydna.utils import shift_location, deduplicate
 
 # We create a dictionary to map ambiguous bases to their consensus base
 # For example, ambigous_base_dict['ACGT'] -> 'N'
@@ -58,12 +58,7 @@ def cre_loxP_overlap(
             value_y = match_y.group()
             if value_x[13:21] == value_y[13:21]:
                 out.append((match_x.start() + 13, match_y.start() + 13, 8))
-    # Unique values (keeping the order)
-    unique_out = []
-    for item in out:
-        if item not in unique_out:
-            unique_out.append(item)
-    return unique_out
+    return deduplicate(out)
 
 
 loxP_dict = {