diff corebio/transform.py @ 0:c55bdc2fb9fa

Uploaded

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/corebio/transform.py	Thu Oct 27 12:09:09 2011 -0400
@@ -0,0 +1,605 @@
+#  Copyright (c) 2006 John Gilman
+#
+#  This software is distributed under the MIT Open Source License.
+#  <http://www.opensource.org/licenses/mit-license.html>
+#
+#  Permission is hereby granted, free of charge, to any person obtaining a 
+#  copy of this software and associated documentation files (the "Software"),
+#  to deal in the Software without restriction, including without limitation
+#  the rights to use, copy, modify, merge, publish, distribute, sublicense,
+#  and/or sell copies of the Software, and to permit persons to whom the
+#  Software is furnished to do so, subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be included
+#  in all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 
+#  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 
+#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+#  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 
+#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+#  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN 
+#  THE SOFTWARE.
+
+""" Transformations of Seqs (alphabetic sequences).
+
+
+
+Classes :
+- Transform   -- Simple transforms of alphabetic strings.
+- GeneticCode -- The genetic mapping of dna to protein.
+
+Functions :
+-  mask_low_complexity -- Implementation of Seg algorithm to remove low complexity  
+        regions from protein sequences.
+   
+    
+"""
+
+
+from corebio.data import dna_extended_letters, dna_ambiguity
+from corebio.seq import Seq, protein_alphabet, nucleic_alphabet, dna_alphabet
+from string import maketrans
+from corebio.moremath import log2 , entropy
+
+__all__ = [
+    'Transform',
+    'mask_low_complexity',
+    'GeneticCode'
+    ]
+
+class Transform(object) :
+    """A translation between alphabetic strings.
+    (This class is not called 'Translation' to avoid confusion with the
+    biological translation of rna to protein.)
+    
+    Example:
+    trans = Transform( 
+        Seq("ACGTRYSWKMBDHVN-acgtUuryswkmbdhvnXx?.~'", dna_alphabet),                    
+        Seq("ACGTRYSWKMNNNNN-acgtUuryswkmbnnnnXx?.~", reduced_nucleic_alphabet)         
+        )
+    s0 = Seq("AAAAAV", nucleic_alphabet)
+    s1 = trans(s0)              
+    assert(s1.alphabet == reduced_nucleic_alphabet)
+    assert(s2 == Seq("AAAAAN",  reduced_nucleic_alphabet)
+        
+    Status : Beta 
+    """
+    
+    __slots__ = ["table", "source", "target"]
+    def __init__(self, source, target) :
+
+        self.table = maketrans(source, target)
+        self.source = source
+        self.target = target
+     
+     
+    def __call__(self, seq) :
+        """Translate sequence."""
+        if not self.source.alphabet.alphabetic(seq) :
+            raise ValueError("Incompatable alphabets")
+        s = str.translate(seq, self.table)
+        cls = self.target.__class__
+        return cls(s, self.target.alphabet, seq.name, seq.description)
+# End class Translation
+
+# FIXME: Test, document, add to seq.
+dna_complement = Transform(
+        Seq("ACGTRYSWKMBDHVN-acgtUuryswkmbdhvnXx?.~", dna_alphabet),  
+        Seq("TGCAYRSWMKVHDBN-tgcaAayrswmkvhdbnXx?.~", dna_alphabet),  
+    )
+
+     
+
+def mask_low_complexity(seq, width =12, trigger=1.8, extension=2.0, mask='X') :
+    """ Mask low complexity regions in protein sequences.
+    
+    Uses the method of Seg [1] by Wootton & Federhen [2] to divide a sequence   
+    into regions of high and low complexity. The sequence is divided into
+    overlapping windows. Low complexity windows either have a sequence entropy
+    less that the trigger complexity, or have an entropy less than the extension    
+    complexity and neighbor other low-complexity windows. The sequence within   
+    low complexity regions are replaced with the mask character (default 'X'), 
+    and the masked alphabetic sequence is returned.
+    
+    The default parameters, width=12, trigger=1.8, extension=2.0, mask='X' are
+    suitable for masking protein sequences before a database search. The 
+    standard default seg parameters are width=12, trigger=2.2, extension=2.5
+    
+    Arguments:
+        Seq seq         -- An alphabetic sequence
+        int width       -- Window width
+        float trigger   -- Entropy in bits between 0 and 4.3.. ( =log_2(20) )
+        float extension -- Entropy in bits between 0 and 4.3.. ( =log_2(20) )
+        char mask       -- The mask character (default: 'X') 
+    Returns :
+        Seq         -- A masked alphabetic sequence
+    Raises :
+        ValueError  -- On invalid arguments
+    Refs:
+        [1] seg man page: 
+            http://bioportal.weizmann.ac.il/education/materials/gcg/seg.html
+        [2] Wootton & Federhen (Computers and Chemistry 17; 149-163, (1993)) 
+    Authors:
+        GEC 2005
+    Future :
+        - Optional mask character.
+        - Option to lower case masked symbols.
+        - Remove arbitary restriction to protein.
+    """
+    
+    lg20 = log2(20)
+    if trigger<0 or trigger>lg20 :
+        raise ValueError("Invalid trigger complexity: %f"% trigger) 
+    if extension<0 or extension>lg20 or extension<trigger:
+        raise ValueError("Invalid extension complexity: %f"% extension)
+    if width<0 :
+        raise ValueError("Invalid width: %d"% width)
+
+    if width > len(seq) : return seq
+    
+    s = seq.ords()
+
+    X = seq.alphabet.ord(mask)
+
+    
+    nwindows = len(seq)- width +1
+    ent = [ 0 for x in range(0, nwindows)]
+    count = [ 0 for x in range(0, len(seq.alphabet) )]
+    
+    for c in s[0:width] : count[c] +=1
+    ent[0] = entropy(count,2)
+    
+    for i in range(1, nwindows) :
+        count[ s[i-1] ] -= 1
+        count[ s[i+width-1] ] +=1
+        ent[i] = entropy(count,2)
+    
+    prev_segged = False 
+    for i in range(0, nwindows) :
+        if ((prev_segged and ent[i]< extension) or 
+            ent[i]< trigger) :
+            for j in range(0, width) : s[i+j]=X
+            prev_segged=True
+        else :
+            prev_segged = False
+
+
+    # Redo, only backwards
+    prev_segged = False 
+    for i in range(nwindows-1, -1, -1) :
+        if ((prev_segged and ent[i]< extension) or 
+            ent[i]< trigger) :
+            for j in range(0, width) : s[i+j]=X
+            prev_segged=True
+        else :
+            prev_segged = False
+
+    
+    return  seq.alphabet.chrs(s)
+# end mask_low_complexity()    
+     
+
+class GeneticCode(object):
+    """An encoding of amino acids by DNA triplets.
+ 
+    Example : 
+    
+    Genetic Code [1]: Standard   
+          T         C         A         G      
+       +---------+---------+---------+---------+
+     T | TTT F   | TCT S   | TAT Y   | TGT C   | T
+     T | TTC F   | TCC S   | TAC Y   | TGC C   | C
+     T | TTA L   | TCA S   | TAA Stop| TGA Stop| A
+     T | TTG L(s)| TCG S   | TAG Stop| TGG W   | G
+       +---------+---------+---------+---------+
+     C | CTT L   | CCT P   | CAT H   | CGT R   | T
+     C | CTC L   | CCC P   | CAC H   | CGC R   | C
+     C | CTA L   | CCA P   | CAA Q   | CGA R   | A
+     C | CTG L(s)| CCG P   | CAG Q   | CGG R   | G
+       +---------+---------+---------+---------+
+     A | ATT I   | ACT T   | AAT N   | AGT S   | T
+     A | ATC I   | ACC T   | AAC N   | AGC S   | C
+     A | ATA I   | ACA T   | AAA K   | AGA R   | A
+     A | ATG M(s)| ACG T   | AAG K   | AGG R   | G
+       +---------+---------+---------+---------+
+     G | GTT V   | GCT A   | GAT D   | GGT G   | T
+     G | GTC V   | GCC A   | GAC D   | GGC G   | C
+     G | GTA V   | GCA A   | GAA E   | GGA G   | A
+     G | GTG V   | GCG A   | GAG E   | GGG G   | G
+       +---------+---------+---------+---------+
+
+    
+    See Also :
+    -- http://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi?mode=c
+    -- http://www.ncbi.nlm.nih.gov/projects/collab/FT/index.html#7.5
+    Authors:
+        JXG, GEC
+    """
+    # TODO: Explain use of '?' in translated sequence.
+    # TODO: Does translate fails with aproriate execption when fed gaps?
+    # TODO: Can back_translate handle gaps?
+    
+    def __init__(self, ident, description,
+        amino_acid, start, base1, base2, base3):
+        """Create a new GeneticCode.
+
+        Args:
+        -- ident - Standarad identifier (Or zero). An integer
+        -- description 
+        -- amino acid - A sequecne of amino acids and stop codons. e.g.
+            "FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG"
+        -- start - A sequence indicating start codons, e.g.,
+            "---M---------------M---------------M----------------------------"
+        -- base1 - The first base of each codon. e.g., 
+            "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG"
+        -- base2 - The second base of each codon. e.g.,
+            "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG"
+        -- base3 - The last base of each codon. e.g., 
+            "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"            
+        """
+        self.ident = ident
+        self.description = description
+   
+        self.amino_acid = amino_acid
+        self.start = start
+        self.base1 = base1
+        self.base2 = base2
+        self.base3 = base3
+    
+        stop_codons = []
+        start_codons = []
+        for i, a in enumerate(amino_acid) :
+            codon = base1[i] + base2[i] + base3[i]
+            if a=='*' :  stop_codons.append(codon)
+            if start[i] == 'M': start_codons.append(codon)
+            
+        self.stop_codons = tuple(stop_codons)
+        self.start_codons = tuple(start_codons)
+        
+        # Building the full translation table is expensive,
+        # so we avoid doing so until necessary.
+        self._table = None
+        self._back_table = None
+
+    #@staticmethod
+    def std_list():
+        "Return a list of standard genetic codes."
+        return _codon_tables
+    std_list = staticmethod(std_list)
+
+    #@staticmethod
+    def std():
+        "The standard 'universal' genetic code."
+        return _codon_tables[0]
+    std = staticmethod(std)
+
+    
+    #@staticmethod
+    def by_name(name) :
+        """Find a genetic code in the code list by name or identifier.
+        """
+        for t in _codon_tables :
+            if t.ident == name or t.description == name :
+                return t
+        raise ValueError("No such translation table: %s" % str(name) )
+    by_name = staticmethod(by_name)        
+    
+  
+    def _get_table(self) :
+        if self._table is None : self._create_table() 
+        return self._table  
+    table = property(_get_table, None, "A map between codons and amino acids")
+
+    def _get_back_table(self) :
+        if self._back_table is None : 
+            self._create_table() 
+        return self._back_table  
+    back_table = property(_get_back_table, None, "A map between amino acids and codons")
+
+
+    def _create_table(self) :
+        aa = self.amino_acid
+        base1 = self.base1
+        base2 = self.base2
+        base3 = self.base3
+        
+        # Construct a table of unambiguous codon translations
+        table = {}
+        for i, a in enumerate(aa) :
+            codon = base1[i] + base2[i] + base3[i]
+            table[codon] = a
+        
+        # Build the back table.
+        back_table = {}
+        items = table.items()
+        items.sort()
+        for codon, aa in items[::-1] :
+            back_table[aa] = codon   # Use first codon, alphabetically.
+        back_table['X'] = 'NNN'
+        back_table['B'] = 'NNN'         
+        back_table['Z'] = 'NNN'         
+        back_table['J'] = 'NNN'         
+        self._back_table = back_table
+                
+        ltable = {}
+        letters = dna_extended_letters+'U' # include RNA in table
+
+        # Create a list of all possble codons
+        codons = []
+        for c1 in letters:
+            for c2 in letters:
+                for c3 in letters :
+                    codons.append( c1+c2+c3)        
+
+        # For each ambiguous codon, construct all compatible unambiguous codons.
+        # Translate and collect a set of all possible translated amino acids.
+        # If more than one translation look for possible amino acid ambiguity       
+        # codes. 
+        for C in codons :
+            translated = dict() # Use dict, because no set in py2.3
+            c = C.replace('U', 'T') # Convert rna codon to dna
+            for c1 in dna_ambiguity[c[0]]:
+                for c2 in dna_ambiguity[c[1]]:
+                    for c3 in dna_ambiguity[c[2]]:
+                        aa = table[ c1+c2+c3 ]
+                        translated[aa] = ''
+            translated = list(translated.keys())
+            translated.sort()
+            if len(translated) ==1 :
+                trans = list(translated)[0]
+            elif translated == ['D','N'] :
+                trans = 'B'      
+            elif translated == ['E','Q'] :
+                trans = 'Z' 
+            elif translated == ['I','L'] :
+                trans = 'J'             
+            elif '*' in translated:
+                trans = '?'
+            else :
+                trans = 'X'
+            ltable[C] = trans
+
+        self._table = ltable
+    # End create tables
+
+    def translate(self, seq, frame=0) :
+        """Translate a DNA sequence to a polypeptide using full
+        IUPAC ambiguities in DNA/RNA and amino acid codes.
+        
+        Returns : 
+        -- Seq - A polypeptide sequence 
+        """
+        # TODO: Optimize.
+        # TODO: Insanity check alphabet.
+        seq = str(seq)
+        table = self.table
+        trans = []
+        L = len(seq)
+        for i in range(frame, L-2, 3) :   
+            codon = seq[i:i+3].upper()
+            trans.append( table[codon])
+        return Seq(''.join(trans), protein_alphabet)
+
+             
+    def back_translate(self, seq) :
+        """Convert protein back into coding DNA.
+        
+        Args:
+        -- seq - A polypeptide sequence.
+        
+        Returns :
+        -- Seq - A dna sequence
+        """
+        # TODO: Optimzie
+        # TODO: Insanity check alphabet.
+        table = self.back_table
+        seq = str(seq)
+        trans = [ table[a] for a in seq]
+        return Seq(''.join(trans), dna_alphabet)
+        
+ #TODO: translate_orf(self, seq, start) ?
+ #TODO: translate_to_stop(self, seq, frame) ?       
+ #TODO: translate_all_frames(self,seq) -> 6 translations.
+ 
+    def __repr__(self) :
+        string = []
+        string += 'GeneticCode( %d, "' % self.ident
+        string += self.description
+        string += '", \n'
+        string += '    amino_acid = "'
+        string += self.amino_acid
+        string += '",\n'
+        string += '    start =      "'
+        string += self.start
+        string += '",\n'
+        string += '    base1 =      "'
+        string += self.base1
+        string += '",\n'
+        string += '    base2 =      "'
+        string += self.base2
+        string += '",\n'
+        string += '    base3 =      "'
+        string += self.base3
+        string += '" )'
+        return ''.join(string)
+        
+        
+    def __str__(self) :
+        """Returns a text representation of this genetic code."""
+        # Inspired by http://bugzilla.open-bio.org/show_bug.cgi?id=1963
+        letters = "TCAG" # Convectional ordering for codon tables.
+        string = []
+        
+        if self.ident :
+            string += 'Genetic Code [%d]: ' % self.ident
+        else :
+            string += 'Genetic Code: '
+        string +=  self.description or ''        
+
+        string += "\n    "
+        string += " ".join( ["  %s      " % c2 for c2 in letters] ) 
+        
+        string += "\n   +" 
+        string +=  "+".join(["---------" for c2 in letters]) + "+  "
+        
+        table = self.table
+        
+        for c1 in letters :
+            for c3 in letters :
+                string += '\n '
+                string  += c1 
+                string  += " |"
+                for c2 in letters :
+                    codon = c1+c2+c3
+                    string += " " + codon
+                    if codon in self.stop_codons :
+                        string  += " Stop|"
+                    else :
+                        amino = table.get(codon, '?')
+                        if codon in self.start_codons :
+                            string += " %s(s)|" % amino
+                        else :
+                            string += " %s   |" % amino
+                string += " " + c3
+                
+            string += "\n   +"
+            string += "+".join(["---------" for c2 in letters]) 
+            string += "+  "
+        string += '\n'
+        return ''.join(string)
+# end class GeneticCode
+
+ 
+# Data from http://www.ncbi.nlm.nih.gov/projects/collab/FT/index.html#7.5
+# Aug. 2006
+# Genetic Code Tables
+# 
+# Authority      International Sequence Databank Collaboration
+# Contact        NCBI
+# Scope          /transl_table qualifier
+# URL            http://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi?mode=c   
+_codon_tables = ( 
+    GeneticCode(1, "Standard",
+        "FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "---M---------------M---------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+        
+    GeneticCode(2, "Vertebrate Mitochondrial",
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSS**VVVVAAAADDEEGGGG",
+        "--------------------------------MMMM---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+ 
+    GeneticCode(3, "Yeast Mitochondrial",
+        "FFLLSSSSYY**CCWWTTTTPPPPHHQQRRRRIIMMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "----------------------------------MM----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"), 
+
+    GeneticCode(4, "Mold, Protozoan, Coelenterate Mitochondrial & Mycoplasma/Spiroplasma",
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "--MM---------------M------------MMMM---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+        
+    GeneticCode(5, "Invertebrate Mitochondrial", 
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSSSSVVVVAAAADDEEGGGG",
+        "---M----------------------------MMMM---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(6, "Ciliate, Dasycladacean and Hexamita Nuclear",    
+        "FFLLSSSSYYQQCC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+ 
+    GeneticCode(9, "Echinoderm and Flatworm Mitochondrial", 
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIIMTTTTNNNKSSSSVVVVAAAADDEEGGGG",
+        "-----------------------------------M---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(10, "Euplotid Nuclear",
+        "FFLLSSSSYY**CCCWLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+  
+    GeneticCode(11, "Bacterial and Plant Plastid",
+        "FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "---M---------------M------------MMMM---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(12, "Alternative Yeast Nuclear",
+        "FFLLSSSSYY**CC*WLLLSPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-------------------M---------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+                                                                   
+    GeneticCode(13,"Ascidian Mitochondrial", 
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSSGGVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(14, "Alternative Flatworm Mitochondrial",
+        "FFLLSSSSYYY*CCWWLLLLPPPPHHQQRRRRIIIMTTTTNNNKSSSSVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(15, "Blepharisma Nuclear",
+        "FFLLSSSSYY*QCC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(16, "Chlorophycean Mitochondrial",
+        "FFLLSSSSYY*LCC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(21, "Trematode Mitochondrial",
+        "FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNNKSSSSVVVVAAAADDEEGGGG",
+        "-----------------------------------M---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(22, "Scenedesmus obliquus Mitochondrial",
+        "FFLLSS*SYY*LCC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "-----------------------------------M----------------------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG"),
+
+    GeneticCode(23,"Thraustochytrium Mitochondrial",
+        "FF*LSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG",
+        "--------------------------------M--M---------------M------------",
+        "TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG",
+        "TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG",
+        "TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG",),
+    )
+    
+          
+        
+           
\ No newline at end of file