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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<meta content="text/html; charset=ISO-8859-1"
http-equiv="content-type">
<title>Restriction.html</title>
</head>
<body vlink="#ff0000" alink="#000088" link="#0000ff"
style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);">
<h2><a class="mozTocH2" name="mozTocId419365"></a><span class="mozTocH2"></span>
Working
with restriction enzymes</h2>
<big style="font-weight: bold;"><br>
Table of content<br>
</big>
<ul id="mozToc">
<!--mozToc h1 1 h2 2 h3 3 h4 4 h5 5 h6 6--><li><a href="#mozTocId419365">
Working
with restriction enzymes</a>
<ul>
<li>
<ul>
<li><a href="#mozTocId101269">1 The
restriction enzymes classes </a>
<ul>
<li><a href="#mozTocId59051">1.1
Importing the enzymes</a></li>
<li><a href="#mozTocId868359">1.2
Naming convention </a></li>
<li><a href="#mozTocId447698">1.3
Searching for restriction sites</a></li>
<li><a href="#mozTocId29937">1.4
Retrieving the sequences produced by a digestion</a></li>
<li><a href="#mozTocId255275">1.5
Analysing circular sequences</a></li>
<li><a href="#mozTocId25220">1.6 Comparing enzymes with
each others </a></li>
<li><a href="#mozTocId724099">1.7
Other
facilities provided by the enzyme classes</a></li>
</ul>
</li>
<li><a href="#mozTocId343319">2
The
RestrictionBatch class : a class to deal with several enzymes </a>
<ul>
<li><a href="#mozTocId32850">2.1
Creating a RestrictionBatch </a></li>
<li><a href="#mozTocId672810">2.2
Restricting a RestrictionBatch to a particular supplier</a></li>
<li><a href="#mozTocId436678">2.3
Adding enzymes to a RestrictionBatch </a></li>
<li><a href="#mozTocId432981">2.4
Removing enzymes from a RestrictionBatch</a></li>
<li><a href="#mozTocId479498">2.5
Manipulating RestrictionBatch</a></li>
<li><a href="#mozTocId919079">2.6
Analysing sequences with a RestrictionBatch </a></li>
<li><a href="#mozTocId114148">2.7
Other
RestrictionBatch methods </a></li>
</ul>
</li>
<li><a href="#mozTocId569237">3 AllEnzymes
and CommOnly : two
preconfigured RestrictionBatches </a></li>
<li><a href="#mozTocId960354">4 The Analysis
class : even simpler
restriction analysis </a>
<ul>
<li><a href="#mozTocId994414">4.1 Setting up an
Analysis</a></li>
<li><a href="#mozTocId129244">4.2 Full restriction
analysis </a></li>
<li><a href="#mozTocId441271">4.3 Changing the title </a></li>
<li><a href="#mozTocId450266">4.4 Customising the
output </a></li>
<li><a href="#mozTocId864311">4.5 Fancier
restriction analysis </a></li>
<li><a href="#mozTocId289477">4.6 More complex
analysis </a></li>
</ul>
</li>
<li><a href="#mozTocId343319">5
Advanced features : the FormattedSeq class </a>
<ul>
<li><a href="#mozTocId74092">5.1 Creating a
FormattedSeq </a></li>
<li><a href="#mozTocId143837">5.2 Unlike Bio.Seq,
FormattedSeq retains information about their shape </a></li>
<li><a href="#mozTocId123270">5.3 Changing the
shape of a FormattedSeq </a></li>
<li><a href="#mozTocId710376">5.4 Using / and //
operators with FormattedSeq </a></li>
</ul>
</li>
<li><a href="#mozTocId80946">6 More advanced
features </a>
<ul>
<li><a href="#mozTocId546339">6.1 Updating the
enzymes from Rebase : rebase_update.py </a></li>
<li><a href="#mozTocId49285">6.2 Compiling a new
dictionary : the script ranacompiler.py </a></li>
<li><a href="#mozTocId968583">6.3 Subclassing
the class Analysis </a></li>
</ul>
</li>
<li><a href="#mozTocId114111">7 Limitation
and caveat </a>
<ul>
<li><a href="#mozTocId218594">7.1 All DNA are non
methylated </a></li>
<li><a href="#mozTocId790484">7.2 No support for
star activity </a></li>
<li><a href="#mozTocId218334">7.3 Safe to use with
degenerated DNA </a></li>
<li><a href="#mozTocId49392">7.4 Non standard bases
in DNA are not
allowed </a></li>
<li><a href="#mozTocId395117">7.5 Sites found at
the edge of linear
DNA might not be accessible in a real digestion </a></li>
<li><a href="#mozTocId112206">7.6 Restriction
reports cutting sites
not enzyme recognition sites </a></li>
</ul>
</li>
<li><a href="#mozTocId386540">8 Annexe :
modifying dir() to use
with from Bio.Restriction import * </a></li>
</ul>
</li>
</ul>
</li>
</ul>
<big style="font-weight: bold;"><br>
</big><br>
<br>
<h3><a class="mozTocH3" name="mozTocId101269"></a>1 The
restriction enzymes classes<br>
</h3>
<br>
The restriction enzyme
package is situated in Bio/Restriction. This package will allow you to
work with restriction enzymes and realise restriction analysis on your
sequence. Restriction make use of the facilities offered by Rebase and
contains classes for more than 600 restriction enzymes. This chapter
will lead you through a quick overview of the facilities offered by the
Restriction package of biopython. The chapter is constructed as an
interactive python session and the best way to read it is with a python
shell open alongside you.<br>
<h4><a class="mozTocH4" name="mozTocId59051"></a><span class="mozTocH4"></span>1.1
Importing the enzymes</h4>
To import the enzymes, open a python shell and type :<br>
<pre>>>> from Bio import Restriction<br>>>> dir()<br>['Restriction', '__builtins__', '__doc__', '__name__']<br>>>> Restriction.EcoRI<br>EcoRI<br>>>> Restriction.EcoRI.site<br>'GAATTC'<br>>>><br></pre>
You will certainly notice that the package is quite slow to load. This
is normal as each enzyme possess its own class and there is a lot of
them. This will not affect the speed of python after the initial
import. <br>
<br>
I don't know for you but I find it quite cumbersome to have to prefix
each operation with <span style="font-family: monospace;">Restriction.</span>,
so here is another way to import
the package.<br>
<pre>>>> from Bio.Restriction import *<br>>>> EcoRI<br>EcoRI<br>>>> EcoRI.site<br>'GAATTC'<br>>>></pre>
However, this method has one big disadvantage :<br>
It
is almost impossible to use the command 'dir()' anymore as there is
so much enzymes the results is hardly readable. A workaround is
provided at the end of this tutorial. I let you decide which method you
prefer. But in this tutorial I
will use the second. If you prefer the first method you will need to
prefix each call to a restriction enzyme with 'Restriction.' in the
remaining of the tutorial.<br>
<h4><a class="mozTocH4" name="mozTocId868359"></a><span class="mozTocH4"></span>1.2
Naming convention<br>
</h4>
To access an Enzyme simply enter
it's name. You must respect the usual naming convention with the upper
case letters and Latin numbering (in upper case as well):<br>
<pre>>>> EcoRI <br>EcoRI<br>>>> ecori<br><br>Traceback (most recent call last):<br> File "<pyshell#25>", line 1, in -toplevel-<br> ecori<br>NameError: name 'ecori' is not defined<br>>>> EcoR1<br><br>Traceback (most recent call last):<br> File "<pyshell#26>", line 1, in -toplevel-<br> EcoR1<br>NameError: name 'EcoR1' is not defined<br>>>> KpnI<br>KpnI<br>>>><br></pre>
ecori or EcoR1 are not enzymes, EcoRI and KpnI are.<br>
<h4><a class="mozTocH4" name="mozTocId447698"></a><span class="mozTocH4"></span>1.3
Searching for restriction sites</h4>
So what can we do with these restriction enzymes. To see that we
will
need a DNA sequence. Restriction enzymes support both <span
style="font-family: monospace;">Bio.Seq.MutableSeq</span> and <span
style="font-family: monospace;">Bio.Seq.Seq</span> objects. You can
use any DNA
alphabet which complies with the IUPAC
alphabet.
<pre>>>> from Bio.Seq import Seq<br>>>> from Bio.Alphabet.IUPAC import IUPACAmbiguousDNA<br>>>> amb = IUPACAmbiguousDNA()<br>>>> my_seq = Seq('AAAAAAAAAAAAAA', amb)<br>>>> my_seq<br>Seq('AAAAAAAAAAAAAA', IUPACAmbiguousDNA())<br></pre>
Searching a sequence for the presence of restriction site for your
preferred enzyme is as simple as :<br>
<pre>>>> EcoRI.search(my_seq)<br>[]<br></pre>
The results is a list. Here the list is empty since there is
obviously no site EcoRI site in my_seq. Let's try to get a
sequence
with a EcoRI site.<br>
<pre>>>> ecoseq = my_seq + Seq(EcoRI.site, amb) + my_seq<br>>>> ecoseq<br>Seq('AAAAAAAAAAAAAAGAATTCAAAAAAAAAAAAAA', IUPACAmbiguousDNA())<br>>>> EcoRI.search(ecoseq)<br>[16]<br></pre>
We therefore have a site at position 16 of the sequence ecoseq. The
position returned by the method search is the first base of the
downstream segment produced by a restriction (i.e. the first base after
the position where the enzyme will cut). The Restriction
package follows biological convention (the first base of a sequence is
base 1). No need to make difficult conversions between your recorded
biological data and the results produced by the enzymes in this
package.<br>
<h4><a class="mozTocH4" name="mozTocId29937"></a><span class="mozTocH4"></span>1.4
Retrieving the sequences produced by a digestion</h4>
Seq objects as all python sequence, have different conventions and the
first base of a sequence is base 0. Therefore to get the sequences
produced by an EcoRI digestion of ecoseq, one should do the following :<br>
<pre>>>> ecoseq[:15], ecoseq[15:] <br>(Seq('AAAAAAAAAAAAAAG', IUPACAmbiguousDNA()), Seq('AATTCAAAAAAAAAAAAAA', IUPACAmbiguousDNA())) <br></pre>
I hear you thinking "this is a cumbersome and error prone method to get
these sequences". To simplify your life, enzymes provide another
method to get theses sequences
without hassle : <span style="font-family: monospace;">catalyse</span>.
This method will return a tuple containing
all the fragments produced by a complete digestion of the sequence.
Using it is as simple as before :<br>
<pre>>>> EcoRI.catalyse(ecoseq)<br>(Seq('AAAAAAAAAAAAAAG', IUPACAmbiguousDNA()), Seq('AATTCAAAAAAAAAAAAAA', IUPACAmbiguousDNA()))</pre>
<h4><a class="mozTocH4" name="mozTocId255275"></a><span class="mozTocH4"></span>1.5
Analysing circular sequences</h4>
Now, if you have entered the previous command in your shell you may
have noticed that both 'search' and 'catalyse' can take a second
argument 'linear' which default to True. Using this will allow you to
simulate circular sequences such as plasmids. Setting linear to False
inform the enzyme to make the search over a circular sequence and to
search for potential sites spanning over the boundaries of the sequence.<br>
<pre>>>> EcoRI.search(ecoseq, linear=False)<br>[16]<br>>>> EcoRI.catalyse(ecoseq, linear=False)<br>(Seq('AATTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAG', IUPACAmbiguousDNA()),)<br>>>> ecoseq # for memory<br>Seq('AAAAAAAAAAAAAAGAATTCAAAAAAAAAAAAAA', IUPACAmbiguousDNA())</pre>
OK, this is quite a difference, we only get one fragment, which
correspond to the linearised sequence. The beginning sequence has been
shifted to take this fact into account. Moreover we can see another
difference :<br>
<pre>>>> new_seq = Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA())<br>>>> EcoRI.search(new_seq)<br>[]<br>>>> EcoRI.search(new_seq, linear=False)<br>[33]<br></pre>
As you can see using 'linear=False', make a site appears in the
sequence new_seq. This site does not exist in a linear sequence as the
EcoRI site is split into two halves at the start and the end of the
sequence. In a circular sequence however, the site is effectively
present when the beginning and end of the sequence are joined.<br>
<h4><a class="mozTocH4" name="mozTocId25220"></a>1.6 Comparing enzymes
with each others<br>
</h4>
Restriction Enzymes define 4 comparative operators ==, !=, >> and
%. All these operator compares two enzymes together and either return
True or False.<br>
<br>
== :<br>
<br>
It will return True if the two sides of the operator are the same. same
is defined as : same name, same site, same overhang (i.e. the only
thing which is equal to EcoRI is EcoRI).<br>
<br>
!= :<br>
<br>
It will return True if the two sides of the operator are different. Two
enzymes are not different if the result produced by one enzyme will
always be the same as the result produced by the other (i.e. True
isoschizomers will not being the same enzymes, are not different since
they are interchangeable).<br>
<br>
>> :<br>
<br>
True if the enzymes recognise the same site, but cut it in a different
way (i.e. the enzymes are neoschizomers).<br>
<br>
% :<br>
<br>
Test the compatibility of the ending produced by the enzymes. (will be
True if the fragments produced with one of the enzyme can directly be
ligated to fragments produced by the other).<br>
<br>
Let's use Acc65I and its isoschizomers as example :<br>
<pre>>>> Acc65I.isoschizomers()<br>[Asp718I, KpnI]<br>>>> Acc65I.elucidate()<br>'G^GTAC_C'<br>>>> Asp718I.elucidate()<br>'G^GTAC_C'<br>>>> KpnI.elucidate()<br>'G_GTAC^C'<br>>>> # Asp718I and Acc65I are True isoschizomers, <br>>>> # they recognise the same site and cut it the <br>>>> # same way.<br>>>> # KpnI is a neoschizomers of the 2 others.<br>>>> # here is the results of the 4 operator<br>>>> # for each pair of enzymes<br>>>> <br>>>> ############# x == y (x is y)<br>>>> Acc65I == Acc65I # same enzyme => True<br>True<br>>>> Acc65I == KpnI # all other cases => False<br>False<br>>>> Acc65I == Asp718I<br>False<br>>>> Acc65I == EcoRI<br>False<br>>>> ############ x != y (x and y are not true isoschizomers)<br>>>> Acc65I != Acc65I # same enzyme => False<br>False<br>>>> Acc65I != Asp718I # different enzymes, but cut same manner => False<br>False<br>>>> Acc65I != KpnI # all other cases => True<br>True<br>>>> Acc65I != EcoRI<br>True<br>>>> ########### x >> y (x is neoschizomer of y)<br>>>> Acc65I >> Acc65I # same enzyme => False<br>False<br>>>> Acc65I >> Asp718I # same site, same cut => False<br>False<br>>>> Acc65I >> EcoRI # different site => False<br>False<br>>>> Acc65I >> KpnI # same site, different cut => True<br>True <br>>>> ########### x % y (fragments produced by x and fragments produced by y<br>>>> # can be directly ligated to each other)<br>>>> Acc65I % Asp718I<br>True<br>>>> Acc65I % Acc65I<br>True<br>>>> Acc65I % KpnI # KpnI -> '3 overhang, Acc65I-> 5' overhang => False <br>False<br>>>><br>>>> SunI.elucidate()<br>'C^GTAC_G'<br>>>> SunI == Acc65I<br>False<br>>>> SunI != Acc65I<br>True<br>>>> SunI >> Acc65I<br>False<br>>>> SunI % Acc65I # different site, same overhang (5' GTAC) => True<br>True<br>>>> SmaI % EcoRV # 2 Blunt enzymes, all blunt enzymes are compatible => True<br>True<br></pre>
<h4><a class="mozTocH4" name="mozTocId724099"></a>1.7
Other
facilities provided by the enzyme classes</h4>
The restriction enzymes class provided quite a number of others
methods. We will not go through all of them, but only have a quick look
to the most useful ones. <br>
<br>
Not all enzymes possess the same properties when it comes to the way
they digest a DNA. If you want to know more about the way a particular
enzyme cut you can use the three following methods. They are fairly
straightforward to understand and refer to the ends that the enzyme
produces blunt, 5' overhanging (also called 3' recessed) sticky end and
3' overhanging (or 5' recessed) sticky end.<br>
<pre>>>> EcoRI.is_blunt()<br>False<br>>>> EcoRI.is_5overhang()<br>True<br>>>> EcoRI.is_3overhang()<br>False<br></pre>
A more detailled view of the restriction site can be produced using the
<span style="font-family: monospace;">elucidate()</span> method. the
"^" refers to the position of the cut in the
sense strand of the sequence. "_" to the cut on the antisense or
complementary strand. "^_" means blunt.
<pre>>>> EcoRI.elucidate()<br>'G^AATT_C'<br>>>> KpnI.elucidate()<br>'G_GTAC^C'<br>>>> EcoRV.elucidate()<br>'GAT^_ATC'<br></pre>
The method frequency will give you the statiscal <span
style="font-family: monospace;">frequency()</span> of the
enzyme site. <br>
<pre>>>> EcoRI.frequency()<br>4096<br>>>> XhoII.elucidate()<br>'R^GATC_Y'<br>>>> XhoII.frequency()<br>1024 </pre>
To get the length of a the recognition sequence of an enzyme use the
built-in function <span style="font-family: monospace;">len()</span> :<br>
<pre>>>> len(EcoRI)<br>6<br>>>> BstXI.elucidate()<br>'CCAN_NNNN^NTGG'<br>>>> len(BstXI)<br>12<br>>>> FokI.site<br>'GGATG'<br>>>> FokI.elucidate() # FokI cut well outside its recognition site<br>'GGATGNNNNNNNNN^NNNN_N'<br>>>> len(FokI) # its length is the length of the recognition site <br>5</pre>
Also interesting are the methods dealing with isoschizomers.
For memory, two enzymes are isoschizomers if they share a same
recognition site. <br>
A further division is made between isoschizomers (same name, recognise
the same
sequence and cut the same way) and neoschizomers which cut at different
positions. equischizomer is an arbitrary choice to design
"isoschizomers_that_are_not_neoschizomers" as this last one was a bit
long.<br>
Another set of method <span style="font-family: monospace;">one_enzyme.is_*schizomers(one_other_enzyme)</span>,
allow to test 2
enzymes against each other.<br>
<pre>>>> Acc65I.isoschizomers()<br>[Asp718I, KpnI]<br>>>> Acc65I.neoschizomers()<br>[KpnI]<br>>>> Acc65I.equischizomers()<br>[Asp718I]<br>>>> KpnI.elucidate()<br>'G_GTAC^C'<br>>>> Acc65I.elucidate()<br>'G^GTAC_C'<br>>>> KpnI.is_neoschizomer(Acc65I)<br>True<br>>>> KpnI.is_neoschizomer(KpnI)<br>False<br>>>> KpnI.is_isoschizomer(Acc65I)<br>True<br>>>> KpnI.is_isoschizomer(KpnI)<br>True<br>>>> KpnI.is_equischizomer(Acc65I)<br>False<br>>>> KpnI.is_equischizomer(KpnI)<br>True<br></pre>
<span style="font-family: monospace;">suppliers()</span> will get you
the list of all the suppliers of the enzyme. <span
style="font-family: monospace;">all_suppliers()</span> will give you
all the suppliers in the database.<br>
<br>
<h3><a class="mozTocH3" name="mozTocId343319"></a><span class="mozTocH3"></span>2
The
RestrictionBatch class : a class to deal with several enzymes<br>
</h3>
If you want to
make a restriction map of a sequence, using individual enzymes can
become tedious and will endures a big overhead due to the repetitive
conversion of the sequence to a FormattedSeq. Restriction provides a
class to make easier the use of
large number of enzymes in one go : RestrictionBatch.<br>
RestrictionBatch will help you to manipulate lots of enzymes with a
single command. Moreover all the enzymes in the restrictionBatch will
share the same converted sequence, reducing the overhead to <br>
<h4><a class="mozTocH4" name="mozTocId32850"></a><span class="mozTocH4"></span>2.1
Creating a RestrictionBatch<br>
</h4>
You can initiate a
restriction batch by passing it a list of enzymes or enzymes name as
argument.
<pre>>>> rb = RestrictionBatch([EcoRI])<br>>>> rb<br>RestrictionBatch(['EcoRI'])<br>>>> rb2 = RestrictionBatch(['EcoRI'])<br>RestrictionBatch(['EcoRI'])<br>>>> rb == rb2<br>True<br></pre>
Adding a new enzyme to a restriction batch is easy :<br>
<pre>>>> rb.add(KpnI)<br>>>> rb<br>RestrictionBatch(['EcoRI', 'KpnI'])<br>>>> rb += EcoRV<br>>>> rb<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI'])])<br></pre>
Another way to create a RestrictionBatch is by simply adding
restriction enzymes together, this is particularly useful for small
batches :<br>
<pre>>>> rb3 = EcoRI + KpnI + EcoRV<br>>>> rb3<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI'])<br></pre>
<h4><a class="mozTocH4" name="mozTocId672810"></a><span class="mozTocH4"></span>2.2
Restricting a RestrictionBatch to a particular supplier</h4>
The Restriction package is based upon the Rebase database. This
database gives a list of suppliers for each enzyme. It would be a shame
not to make use of this facility. You can Produce a RestrictionBatch
containing only enzymes from one or a few supplier(s). Here is how to
do it :<br>
<pre>>>> rb_supp = RestrictionBatch(first=[], suppliers=['A','C','E','G','F','I','H','K','J','M','O','N','Q','P','S','R','U','V','X'])<br>>>> # This will create a RestrictionBatch with the all enzymes which possess a supplier. </pre>
The argument 'suppliers' take a list of one or several single letter
codes corresponding to the supplier(s). The codes are the same as
defined in Rebase. As it would be a pain to have to remember each
supplier code, RestrictionBatch provides a method which show the pair
code <=> supplier :<br>
<pre>>>> RestrictionBatch.show_codes() # as of july 2004 Rebase release.<br>A = Amersham Pharmacia Biotech<br>C = Minotech Biotechnology<br>E = Stratagene<br>G = Qbiogene<br>F = Fermentas AB<br>I = SibEnzyme Ltd.<br>H = American Allied Biochemical, Inc.<br>K = Takara Shuzo Co. Ltd.<br>J = Nippon Gene Co., Ltd.<br>M = Roche Applied Science<br>O = Toyobo Biochemicals<br>N = New England Biolabs<br>Q = CHIMERx<br>P = Megabase Research Products<br>S = Sigma Chemical Corporation<br>R = Promega Corporation<br>U = Bangalore Genei<br>V = MRC-Holland<br>X = EURx Ltd.<br>>>> # You can now choose a code and built your RestrictionBatch<br></pre>
This way of producing a RestrictionBatch can drastically reduce the
amount of useless output from a restriction analysis, limiting the
search to enzymes that you can get hold of and limiting the risks of
nervous breakdown. Nothing is more frustrating than to get the perfect
enzyme for a sub-cloning only to find it's not commercially available.<br>
<h4><a class="mozTocH4" name="mozTocId436678"></a><span class="mozTocH4"></span>2.3
Adding enzymes to a RestrictionBatch<br>
</h4>
Adding an enzyme to a batch if the enzyme is already present will not
raise an exception, but will have no effects. Sometimes you want to get
an enzyme from a RestrictionBatch or add it to the batch if it is not
present.<br>
You will use the get method setting the second argument to True.<br>
<pre>>>> rb3<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI'])<br>>>> rb3.add(EcoRI)<br>>>> rb3<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI'])<br>>>> rb3.get(EcoRI)<br>EcoRI<br>>>> rb3.get(SmaI)<br><br>Traceback (most recent call last):<br> File "<pyshell#4>", line 1, in -toplevel-<br> rb3.get(SmaI)<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1800, in get<br> raise ValueError, 'enzyme %s is not in RestrictionBatch'%e.__name__<br>ValueError: enzyme SmaI is not in RestrictionBatch<br>>>> rb3.get(SmaI, True)<br>SmaI<br>>>> rb3<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI', 'SmaI'])<br></pre>
<h4><a class="mozTocH4" name="mozTocId432981"></a><span class="mozTocH4"></span>2.4
Removing enzymes from a RestrictionBatch</h4>
Removing enzymes from a Batch is done using the <span
style="font-family: monospace;">remove()</span> method. If the
enzyme is not present in the batch this will raise a KeyError. If the
value you want to remove is not an enzyme this will raise a ValueError.<br>
<pre>>>> rb3.remove(EcoRI)<br>>>> rb3<br>RestrictionBatch(['EcoRV', 'KpnI', 'SmaI'])<br>>>> rb3.remove(EcoRI)<br><br>Traceback (most recent call last):<br> File "<pyshell#14>", line 1, in -toplevel-<br> rb3.remove('EcoRI')<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1839, in remove<br> return Set.remove(self, self.format(other))<br> File "/usr/lib/python2.3/sets.py", line 534, in remove<br> del self._data[element]<br>KeyError: EcoRI<br>>>> rb3 += EcoRI<br>>>> rb3 <br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI', 'SmaI'])<br>>>> rb3.remove('EcoRI')<br>>>> rb3<br>RestrictionBatch(['EcoRV', 'KpnI', 'SmaI'])<br>>>> rb3.remove('spam')<br><br>Traceback (most recent call last):<br> File "<pyshell#18>", line 1, in -toplevel-<br> rb3.remove('spam')<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1839, in remove<br> return Set.remove(self, self.format(other))<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1871, in format<br> raise ValueError, '%s is not a RestrictionType'%y.__class__<br>ValueError: <type 'str'> is not a RestrictionType</pre>
<h4><a class="mozTocH4" name="mozTocId479498"></a><span class="mozTocH4"></span>2.5
Manipulating RestrictionBatch</h4>
You can not however add batch together, as they are python sets. You
must use the operator | instead. You can find the intersection between
2 batches using & (see the python documentation about sets for more
information (or import sets; help(sets)).<br>
<pre>>>> rb3 = EcoRI+KpnI+EcoRV<br>>>> rb3<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI'])<br>>>> rb4 = SmaI + PstI<br>>>> rb4<br>RestrictionBatch(['PstI', 'SmaI'])<br>>>> rb3 + rb4<br><br>Traceback (most recent call last):<br> File "<pyshell#23>", line 1, in -toplevel-<br> rb3 + rb4<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1829, in __add__<br> new.add(other)<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1848, in add<br> return Set.add(self, self.format(other))<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 1871, in format<br> raise ValueError, '%s is not a RestrictionType'%y.__class__<br>ValueError: <class 'Bio.Restriction.Restriction.RestrictionBatch'> is not a RestrictionType<br>>>> rb3 | rb4<br>RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI', 'PstI', 'SmaI'])<br>>>> rb3 & rb4<br>RestrictionBatch([])<br>>>> rb4 += EcoRI<br>>>> rb4<br>RestrictionBatch(['EcoRI', 'PstI', 'SmaI'])<br>>>> rb3 & rb4<br>RestrictionBatch(['EcoRI'])<br></pre>
<h4><a class="mozTocH4" name="mozTocId919079"></a><span class="mozTocH4"></span>2.6
Analysing sequences with a RestrictionBatch<br>
</h4>
To analyse a sequence for potential site, you can use the search
method of the batch, the same way you did for restriction enzymes. The
results is no longer a list however, but a dictionary. The keys of the
dictionary are the names of the enzymes and the value a list of
position site. RestrictionBatch does not implement a catalyse method,
as it would not have a real meaning when used with large batch.<br>
<pre>>>> new_seq = Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA())<br>>>> rb.search(new_seq)<br>{'KpnI': [], 'EcoRV': [], 'EcoRI': []}<br>>>> rb.search(new_seq, linear=False)<br>{'KpnI': [], 'EcoRV': [], 'EcoRI': [33]}</pre>
<h4><a class="mozTocH4" name="mozTocId114148"></a><span class="mozTocH4"></span>2.7
Other
RestrictionBatch methods<br>
</h4>
Amongst the other methods provided by RestrictionBatch <span
style="font-family: monospace;">elements()</span> which
return a list of all the element names
alphabetically sorted is certainly the most useful.<br>
<pre>>>> rb = EcoRI + KpnI + EcoRV<br>>>> rb.elements()<br>['EcoRI', 'EcoRV', 'KpnI']</pre>
If you don't care about the alphabetical order use the method <span
style="font-family: monospace;">as_string()</span>, to get the same
thing a bit faster. The list is not sorted.
The order is random as python sets are dictionary.<br>
<pre>>>> rb = EcoRI + KpnI + EcoRV <br>>>> rb.as_string()<br>['EcoRI', 'KpnI', 'EcoRV']</pre>
Other RestrictionBatch methods are generally used for particular
purposes and will not be discussed here. See the source if you are
interested.<span style="font-family: monospace;"></span><br>
<br>
<h3><a class="mozTocH3" name="mozTocId569237"></a>3 AllEnzymes
and CommOnly : two
preconfigured RestrictionBatches<br>
</h3>
While it is sometime practical to produce a RestrictionBatch of your
own you will certainly more frequently use the two batches provided
with the Restriction packages : AllEnzymes and CommOnly. These two
batches contain respectively all the enzymes in the database and only
the enzymes which have a commercial supplier. They are rather big, but
that's what make them useful. With these batch you can produce a full
description of a sequence with a single command. You can use these two
batch as any other batch.<br>
<pre>>>> len(AllEnzymes)<br>671<br>>>> len(CommOnly)<br>589<br>>>> AllEnzymes.search(new_seq) ...</pre>
There is not a lot to say about them apart the fact that they are
present. They are really normal batches, and you can use them as any
other batch.
<h3><a class="mozTocH3" name="mozTocId960354"></a>4 The Analysis
class : even simpler
restriction analysis<br>
</h3>
RestrictionBatch can give you a dictionary with the sites for all the
enzymes in a RestrictionBatch. However, it is sometime nice to
get something a bit easier to read than a python dictionary. Complex
restriction analysis are not easy with RestrictionBatch. Some
refinements in the way to search a sequence for restriction sites will
help. Analysis
provides a serie of command to customise the results obtained from a
pair RestrictionBatch/sequence and some facilities to make the output
sligthly more human readable.<br>
<h4><a class="mozTocH4" name="mozTocId994414"></a>4.1 Setting up an
Analysis</h4>
To build a Restriction Analysis you will need a
RestrictionBatch and a sequence and to tell it if the sequence is
linear or circular. The first argument Analysis take is the
RestrictionBatch, the second is the sequence. If the third argument is
not provided Analysis will assume the sequence is linear.<br>
<pre>>>> new_seq = Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA())<br>>>> rb = RestrictionBatch([EcoRI, KpnI, EcoRV])<br>>>> Ana = Analysis(rb, new_seq, linear=False)<br>>>> Ana<br>Analysis(RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI']),Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA()),False)<br></pre>
<h4><a class="mozTocH4" name="mozTocId129244"></a>4.2 Full restriction
analysis<br>
</h4>
Once you have created your new Analysis, you can use it to get a
restriction analysis of your sequence. The way to make a full
restriction analysis of the sequence is :<br>
<pre>>>> Ana.full()<br>{'KpnI': [], 'EcoRV': [], 'EcoRI': [33]}<br></pre>
This is much the same as the output of a RestrictionBatch.search
method. You will get a more easy to read output with "print_that" used
without argument :<br>
<pre>>>> <br>>>> # let's create a something a bit more complex to analyse.<br>>>><br>>>> rb = RestrictionBatch([], ['A']) # we will explain the meaning of the<br>>>> # double list argument later. <br>>>><br>>>> multi_site = Seq('AAA' + EcoRI.site +'G' + KpnI.site + EcoRV.site + 'CT' +\ <br>SmaI.site + 'GT' + FokI.site + 'GAAAGGGC' + EcoRI.site + 'ACGT', IUPACAmbiguousDNA())<br>>>><br>>>> Analong = Analysis(rb, multi_site) <br>>>> Analong.full()<br>{'EaeI': [], 'CpoI': [], 'AccII': [], 'Bpu1102I': [], 'HindIII': [], 'BalI': [],<br> 'NaeI': [], 'BssHII': [], 'HapII': [27], 'BamHI': [], 'XhoI': [], 'EcoO109I': [<br>], 'XbaI': [], 'SacII': [], 'AvaII': [], 'BbeI': [], 'FokI': [47], 'Eco81I': [],<br> 'BanII': [], 'KpnI': [16], 'NcoI': [], 'FseI': [], 'ApaLI': [], 'NheI': [], 'Ap<br>aI': [], 'AatII': [], 'DraI': [], 'EcoRV': [20], 'BstXI': [], 'HaeIII': [], 'Mlu<br>I': [], 'Aor51HI': [], 'EcoRI': [5, 47], 'AvaI': [26], 'PvuI': [], 'EcoT22I': []<br>, 'PstI': [], 'MvaI': [], 'NotI': [], 'HinfI': [], 'ScaI': [], 'NdeI': [], 'AccI<br>': [], 'MboII': [], 'SnaBI': [], 'SspI': [], 'HhaI': [], 'BglI': [], 'Cfr13I': [<br>], 'SpeI': [], 'AflII': [], 'HpaI': [], 'Van91I': [], 'SfiI': [], 'SphI': [], 'B<br>sp1286I': [], 'SmaI': [28], 'NruI': [], 'FbaI': [], 'AluI': [], 'BglII': [], 'Hi<br>ncII': [], 'StuI': [], 'Sse8387I': [], 'ClaI': [], 'Sau3AI': [], 'MspI': [27], '<br>PshAI': [], 'AfaI': [14], 'MboI': [], 'PmaCI': [], 'SacI': [], 'PvuII': [], 'Eco<br>T14I': [], 'SalI': [], 'BlnI': [], 'TaqI': []}<br>>>><br>>>> # The results are here but it is difficult to read. let's try print_that<br>>>><br>>>> Analong.print_that()<br><br>AfaI : 14.<br>AvaI : 26.<br>EcoRI : 5, 47.<br>EcoRV : 20.<br>FokI : 47.<br>HapII : 27.<br>KpnI : 16.<br>MspI : 27.<br>SmaI : 28.<br><br> Enzymes which do not cut the sequence.<br><br>AatII AccI AccII AflII AluI Aor51HI ApaI ApaLI <br>AvaII BalI BamHI BanII BbeI BglI BglII BlnI <br>Bpu1102I Bsp1286I BssHII BstXI Cfr13I ClaI CpoI DraI <br>EaeI Eco81I EcoO109I EcoT14I EcoT22I FbaI FseI HaeIII <br>HhaI HincII HindIII HinfI HpaI MboI MboII MluI <br>MvaI NaeI NcoI NdeI NheI NotI NruI PmaCI <br>PshAI PstI PvuI PvuII SacI SacII SalI Sau3AI <br>ScaI SfiI SnaBI SpeI SphI Sse8387I SspI StuI <br>TaqI Van91I XbaI XhoI</pre>
Much clearer, is'nt ? The output is optimised for a shell 80 columns
wide. If the output seems odd, check that the width of your shell
is at least 80 columns.<br>
<h4><a class="mozTocH4" name="mozTocId441271"></a>4.3 Changing the title<br>
</h4>
You can provide a title to the analysis and modify the sentence
<span style="font-family: monospace;">'Enzymes which do not cut the
sequence'</span>, by setting the two optional
arguments of <span style="font-family: monospace;">print_that</span>
"title" and "s1". No formating will be
done on these strings so if you have to include the newline (<span
style="font-family: monospace;">'\n'</span>) as
you see fit :<br>
<pre>>>> Analong.print_that(None, title='sequence = multi_site\n\n')<br><br>sequence = multi_site<br><br>AfaI : 14.<br>AvaI : 26.<br>EcoRI : 5, 47.<br>EcoRV : 20.<br>FokI : 47.<br>HapII : 27.<br>KpnI : 16.<br>MspI : 27.<br>SmaI : 28.<br><br> Enzymes which do not cut the sequence.<br><br>AatII AccI AccII AflII AluI Aor51HI ApaI ApaLI <br>AvaII BalI BamHI BanII BbeI BglI BglII BlnI <br>Bpu1102I Bsp1286I BssHII BstXI Cfr13I ClaI CpoI DraI <br>EaeI Eco81I EcoO109I EcoT14I EcoT22I FbaI FseI HaeIII <br>HhaI HincII HindIII HinfI HpaI MboI MboII MluI <br>MvaI NaeI NcoI NdeI NheI NotI NruI PmaCI <br>PshAI PstI PvuI PvuII SacI SacII SalI Sau3AI <br>ScaI SfiI SnaBI SpeI SphI Sse8387I SspI StuI <br>TaqI Van91I XbaI XhoI </pre>
<pre>>>> Analong.print_that(None, <br> title = 'sequence = multi_site\n\n',<br> s1 = '\n no site :\n\n')<br><br>sequence = multi_site<br><br>AfaI : 14.<br>AvaI : 26.<br>EcoRI : 5, 47.<br>EcoRV : 20.<br>FokI : 47.<br>HapII : 27.<br>KpnI : 16.<br>MspI : 27.<br>SmaI : 28.<br><br> no site :<br><br>AatII AccI AccII AflII AluI Aor51HI ApaI ApaLI <br>AvaII BalI BamHI BanII BbeI BglI BglII BlnI <br>Bpu1102I Bsp1286I BssHII BstXI Cfr13I ClaI CpoI DraI <br>EaeI Eco81I EcoO109I EcoT14I EcoT22I FbaI FseI HaeIII <br>HhaI HincII HindIII HinfI HpaI MboI MboII MluI <br>MvaI NaeI NcoI NdeI NheI NotI NruI PmaCI <br>PshAI PstI PvuI PvuII SacI SacII SalI Sau3AI <br>ScaI SfiI SnaBI SpeI SphI Sse8387I SspI StuI <br>TaqI Van91I XbaI XhoI </pre>
<h4><a class="mozTocH4" name="mozTocId450266"></a>4.4 Customising the
output <br>
</h4>
You can modify some aspects of the output interactively. There is three
main type of output,
two listing types (alphabetically sorted and sorted by number of
site) and map-like type. To change the output, use the method <span
style="font-family: monospace;">print_as()</span> of Analysis. The
change of output is permanent for the
instance of Analysis (that is
until the next time you use <span style="font-family: monospace;">print_as()</span>).
The argument of <span style="font-family: monospace;">print_as()</span>
are
strings : <span style="font-family: monospace;">'map'</span>, <span
style="font-family: monospace;">'number'</span> or <span
style="font-family: monospace;">'alpha'</span>. As you have seen
previously the
default behaviour is an
alphabetical list (<span style="font-family: monospace;">'alpha'</span>).<br>
<pre>>>> Analong.print_as('map') <br>>>> Analong.print_that()<br><br> 5 EcoRI<br> | <br> | 14 AfaI<br> | | <br> | | 16 KpnI<br> | | | <br> | | | 20 EcoRV<br> | | | | <br> | | | | 26 AvaI<br> | | | | | <br> | | | | |27 HapII MspI<br> | | | | || <br> | | | | ||28 SmaI<br> | | | | ||| <br> | | | | ||| 47 EcoRI FokI<br> | | | | ||| | <br>AAAGAATTCGGGTACCGATATCCTCCCGGGGTGGATGGAAAGGGCGAATTCACGT<br>|||||||||||||||||||||||||||||||||||||||||||||||||||||||<br>TTTCTTAAGCCCATGGCTATAGGAGGGCCCCACCTACCTTTCCCGCTTAAGTGCA<br>1 55<br><br><br> Enzymes which do not cut the sequence.<br><br>AatII AccI AccII AflII AluI Aor51HI ApaI ApaLI <br>AvaII BalI BamHI BanII BbeI BglI BglII BlnI <br>Bpu1102I Bsp1286I BssHII BstXI Cfr13I ClaI CpoI DraI <br>EaeI Eco81I EcoO109I EcoT14I EcoT22I FbaI FseI HaeIII <br>HhaI HincII HindIII HinfI HpaI MboI MboII MluI <br>MvaI NaeI NcoI NdeI NheI NotI NruI PmaCI <br>PshAI PstI PvuI PvuII SacI SacII SalI Sau3AI <br>ScaI SfiI SnaBI SpeI SphI Sse8387I SspI StuI <br>TaqI Van91I XbaI XhoI <br><br>>>> Analong.print_as('number')<br>>>> Analong.print_that()<br><br><br><br>enzymes which cut 1 times :<br><br>AfaI : 15.<br>AvaI : 27.<br>EcoRV : 21.<br>FokI : 48.<br>HapII : 28.<br>KpnI : 17.<br>MspI : 28.<br>SmaI : 29.<br><br><br>enzymes which cut 2 times :<br><br>EcoRI : 6, 48.<br><br> Enzymes which do not cut the sequence.<br><br>AatII AccI AccII AflII AluI Aor51HI ApaI ApaLI <br>AvaII BalI BamHI BanII BbeI BglI BglII BlnI <br>Bpu1102I Bsp1286I BssHII BstXI Cfr13I ClaI CpoI DraI <br>EaeI Eco81I EcoO109I EcoT14I EcoT22I FbaI FseI HaeIII <br>HhaI HincII HindIII HinfI HpaI MboI MboII MluI <br>MvaI NaeI NcoI NdeI NheI NotI NruI PmaCI <br>PshAI PstI PvuI PvuII SacI SacII SalI Sau3AI <br>ScaI SfiI SnaBI SpeI SphI Sse8387I SspI StuI <br>TaqI Van91I XbaI XhoI <br><br>>>> <br></pre>
To come back to the previous behaviour :<br>
<pre>>>> Analong.print_as('alpha')<br>>>> Analong.print_that()<br><br>AfaI : 14.<br>AvaI : 26.<br>EcoRI : 5, 47.<br>EcoRV : 20.<br>etc ...</pre>
<h4><a class="mozTocH4" name="mozTocId864311"></a>4.5 Fancier
restriction analysis<br>
</h4>
I will not go into the detail for each single method, here are all the
functions that are available. Most are perfectly self explanatory and
the others are fairly well documented (use <span
style="font-family: monospace;">help('Analysis.command_name')</span>).
The methods are :<br>
<pre> full(self,linear=True) <br> blunt(self,dct = None) <br> overhang5(self, dct=None) <br> overhang3(self, dct=None) <br> defined(self,dct=None) <br> with_sites(self, dct=None) <br> without_site(self, dct=None) <br> with_N_sites(self, N, dct=None) <br> with_number_list(self, list, dct=None) <br> with_name(self, names, dct=None) <br> with_site_size(self, site_size, dct=None) <br> only_between(self, start, end, dct=None) <br> between(self,start, end, dct=None) <br> show_only_between(self, start, end, dct=None) <br> only_outside(self, start, end, dct =None) <br> outside(self, start, end, dct=None) <br> do_not_cut(self, start, end, dct =None) <br></pre>
Using these methods is simple :<br>
<pre>>>> new_seq = Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA())<br>>>> rb = RestrictionBatch([EcoRI, KpnI, EcoRV])<br>>>> Ana = Analysis(rb, new_seq, linear=False)<br>>>> Ana<br>Analysis(RestrictionBatch(['EcoRI', 'EcoRV', 'KpnI']),Seq('TTCAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAA', IUPACAmbiguousDNA()),False)<br>>>> Ana.blunt() # output only the result for enzymes which cut blunt<br>{'EcoRV': []}<br>>>> Ana.full() # all the enzymes in the RestrictionBatch<br>{'KpnI': [], 'EcoRV': [], 'EcoRI': [33]}<br>>>> Ana.with_sites() # output only the result for enzymes which have a site in the sequence<br>{'EcoRI': [33]}<br>>>> Ana.without_site() # output only the enzymes which have no site in the sequence<br>{'KpnI': [], 'EcoRV': []}<br>>>> Ana.only_between(1, 20) # the enzymes which cut between the base pairs 1 and 20<br>{}<br>>>> Ana.only_between(20, 34) # etc...<br>{'EcoRI': [33]}<br>>>> Ana.only_outside(20, 34)<br>{}<br>>>> Ana.with_name([EcoRI])<br>{'EcoRI': [33]}<br>>>> </pre>
To get a nice output, you still use <span
style="font-family: monospace;">print_that</span> but this time with
the
command you want executed as argument.<br>
<pre>>>> Ana.print_that(Ana.blunt())<br><br><br> Enzymes which do not cut the sequence.<br><br>EcoRV <br><br>>>> pt = Ana.print_that<br>>>> pt(Ana.with_sites())<br><br>EcoRI : 33.<br><br>>>> pt(Ana.without_site())<br><br><br> Enzymes which do not cut the sequence.<br><br>EcoRV KpnI <br><br>>>> # etc ...<br></pre>
<h4><a class="mozTocH4" name="mozTocId289477"></a>4.6 More complex
analysis<br>
</h4>
All of these methods (except <span style="font-family: monospace;">full()</span>
which, well ... do a full
restriction analysis) can be supplied with an additional dictionary. <br>
If no
dictionary is supplied a full
restriction analysis is used as starting point. Otherwise the
dictionary provided by the argument dct is used. The dictionary must be
formatted as the result of <span style="font-family: monospace;">RestrictionBatch.search</span>.
Therefore of
the form <span style="font-family: monospace;">{'enzyme_name' :
[position1, position2],...}</span>, where
position1 and position2 are integer. All methods list previously output
such dictionaries and can be used as starting point.<br>
<br>
Using this method you can build really complex query by
chaining several method one after the other. For example if
you want all the enzymes which are 5' overhang and cut the sequence
only once, you have two ways to go :<br>
<br>
The hard way consist to build a
RestrictionBatch containing only 5' overhang enzymes and use this batch
to create a new analysis instance and then use the method <span
style="font-family: monospace;">with_N_sites()</span> as follow :<br>
<pre>>>> rbov5 = RestrictionBatch([x for x in rb if x.is_5overhang()])<br>>>> Anaov5 = Analysis(rbov5, new_seq, linear=False)<br>>>> Anaov5.with_N_sites(1)<br>{'EcoRI' : [33]}<br></pre>
The easy solution is to chain several Analysis methods. This is
possible since each method return a dictionary as results and is able
to take a dictionary as input:<br>
<pre>>>> Ana.with_N_sites(1, Ana.overhang5())<br>{'EcoRI': [33]}<br></pre>
The dictionary is always the last argument whatever the command you use.<br>
<br>
The way to prefer certainly depends of the conditions you will use your
Analysis instance. If
you are likely to frequently reuse the same batch with different
sequences, using a dedicated RestrictionBatch might be faster as the
batch is likely to be smaller. Chaining methods is
generally quicker when working with an interactive shell. In a
script, the extended syntax may be easier to understand in a few
months.
<br>
<br>
<h3><a class="mozTocH3" name="mozTocId343319"></a><span class="mozTocH3"></span>5
Advanced features : the FormattedSeq class<br>
</h3>
Restriction enzymes require a much more strict formatting of the DNA
sequences than Bio.Seq object provides. For example, the restriction
enzymes expect to find an ungapped (no space) upper-case sequence,
while Bio.Seq object allow sequences to be in lower-case separated by
spaces. Therefore when a restriction enzyme analyse a Bio.Seq
object (be it a Seq or a MutableSeq), the object undergoes a
conversion. The class FormattedSeq ensure the smooth conversion from
a Bio.Seq object to something which can be safely be used by the
enzyme.<br>
<br>
While this conversion is done automatically by the enzymes if you
provide them with a Seq or a MutableSeq, there is time where it
will be more efficient to realise the conversion before hand. Each time
a Seq object is passed to an enzyme for analysis you pay a overhead due
to the conversion. When analysing the same sequence over and over, it
will be faster to convert the sequence, store the conversion and then
use only the converted sequence. <br>
<h4><a class="mozTocH4" name="mozTocId74092"></a>5.1 Creating a
FormattedSeq<br>
</h4>
Creating a FormattedSeq from a Bio.Seq object is simple. The first
argument of FormattedSeq is the sequence you wish to convert. You can
specify a shape with the second argument linear, if you don't the
FormattedSeq will be linear :
<pre>>>> from Bio.Restriction import *<br>>>> from Bio.Seq import Seq<br>>>> seq = Seq('TTCAAAAAAAAAAGAATTCAAAAGAA')<br>>>> linear_fseq = FormattedSeq(seq, linear=True) <br>>>> default_fseq = FormattedSeq(seq)<br>>>> circular_fseq = FormattedSeq(seq, linear=False)<br>>>> linear_fseq<br>FormattedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=True)<br>>>> linear_fseq.is_linear()<br>True<br>>>> default_fseq.is_linear()<br>True<br>>>> circular_fseq.is_linear()<br>False<br>>>> circular_fseq<br>FormattedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=False)<br></pre>
<h4><a class="mozTocH4" name="mozTocId143837"></a>5.2 Unlike Bio.Seq,
FormattedSeq retains information about their shape<br>
</h4>
FormattedSeq retains information about the shape of the sequence.
Therefore unlike with Seq and MutableSeq you don't need to specify the
shape of the sequence when using <span style="font-family: monospace;">search()</span>
or <span style="font-family: monospace;">catalyse()</span>:<br>
<pre>>>> EcoRI.search(linear_fseq)<br>[15]<br>>>> EcoRI.search(circular_fseq) # no need to specify the shape<br>[15, 25]<br></pre>
In fact, the shape of a FormattedSeq is not altered by the second
argument of the commands search() and catalyse() :<br>
<pre>>>> # In fact the shape is blocked.<br>>>> # The 3 following commands give the same results<br>>>> # which correspond to a circular sequence<br>>>> EcoRI.search(circular_fseq) <br>[15, 25]<br>>>> EcoRI.search(circular_fseq, linear=True)<br>[15, 25]<br>>>> EcoRI.search(circular_fseq, linear=False)<br>[15, 25]<br>>>><br></pre>
<h4><a class="mozTocH4" name="mozTocId123270"></a>5.3 Changing the
shape of a FormattedSeq<br>
</h4>
You can however change the shape of the FormattedSeq. The command to
use are :<br>
<pre>FormattedSeq.to_circular() => new FormattedSeq, shape will be circular. <br>FormattedSeq.to_linear() => new FormattedSeq, shape will be linear<br>FormattedSeq.circularise() => change the shape of FormattedShape to circular<br>FormattedSeq.linearise() => change the shape of FormattedShape to linear<br><br>>>> circular_fseq<br>FormatedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=False)<br>>>> circular_fseq.is_linear()<br>False<br>>>> circular_fseq == linear_fseq<br>False<br>>>> newseq = circular_fseq.to_linear()<br>>>> circular_fseq<br>FormatedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=False)<br>>>> newseq<br>FormatedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=True)<br>>>> circular_fseq.linearise()<br>>>> circular_fseq<br>FormatedSeq(Seq('TTCAAAAAAAAAAGAATTCAAAAGAA', Alphabet()), linear=True)<br>>>> circular_fseq.is_linear()<br>True<br>>>> circular_fseq == linear_fseq<br>True<br>>>> EcoRI.search(circular_fseq) # which is now linear<br>[15]</pre>
<h4><a class="mozTocH4" name="mozTocId710376"></a>5.4 Using / and //
operators with FormattedSeq<br>
</h4>
Not having to specify the shape of the sequence to analyse gives you
the opportunity to use the shorthand '/' and '//' with restriction
enzymes :<br>
<pre>>>> EcoRI/linear_fseq # <=> EcoRI.search(linear_fseq)<br>[15]<br>>>> linear_fseq/EcoRI # <=> EcoRI.search(linear_fseq)<br>[15]<br>>>> EcoRI//linear_fseq # <=> linear_fseq//EcoRI <=> EcoRI.catalyse(linear_fseq)<br>(Seq('TTCAAAAAAAAAAG', Alphabet()), Seq('AATTCAAAAGAA', Alphabet()))<br></pre>
Another way to avoid the overhead due to a repetitive conversion from a
Seq object to a FormattedSeq is to use a RestrictionBatch. <br>
<br>
To conclude, the performance gain achieved when using a FormattedSeq
instead of a Seq is not huge. The analysis of a 10 kb sequence by all
the enzymes in AllEnzymes (<span style="font-family: monospace;">for x
in AllEnzymes : x.search(seq), </span>671 enzymes)<span
style="font-family: monospace;"></span> is 7 % faster when using a
FormattedSeq than a Seq. Using a RestrictionBatch (<span
style="font-family: monospace;">AllEnzymes.search(seq)</span>) is
about as fast as using a FormattedSeq the first time the search is run.
This however is dramatically reduced in subsequent runs with the same
sequence (RestrictionBatch keep in memory the result of their last run
while the sequence is not changed).<br>
<h3><a class="mozTocH3" name="mozTocId80946"></a>6 More advanced
features <br>
</h3>
This chapter addresses some more advanced features of the packages,
most
users can safely ignore it.<br>
<h4><a class="mozTocH4" name="mozTocId546339"></a>6.1 Updating the
enzymes from Rebase : rebase_update.py<br>
</h4>
Most people will certainly not need to update the enzymes. The
restriction enzyme package will be updated in with each new release of
biopython. But if you wish to get an update in between
biopython-releases here is how to do it. Each month, Rebase release a
new compilation of data about restriction enzymes. While the enzymes do
not change so frequently, you may wish to update the restriction
enzymes classes. The first thing to do is to get the last rebase file.
You can find the release of Rebase at <span
style="font-family: monospace;">http://rebase.neb.com/rebase.files.html</span>.
The file you are interested in are in the EMBOSS format. You can
download the files directly from the rebase ftp server using your
browser. The file are situated at <span style="font-family: monospace;">ftp://ftp.neb.com/pub/rebase</span>.
<br>
You will have to download 3 files :<br>
<span
style="font-family: monospace;">emboss_e.###</span><br>
<span
style="font-family: monospace;">emboss_r.###</span><br>
<span
style="font-family: monospace;">emboss_s.###</span><br>
The <span style="font-family: monospace;">###</span> is a 3 digit
number corresponding to the year and month of the release. The first
digit is the year, the two last are the month : so July 2004 will be :
407; October 2005 : 510, etc... Download the three file corresponding
to the current month and place them in a folder. <br>
<br>
Another way to do the same thing is to use the <span
style="font-family: monospace;">rebase_update.py</span>. script
provided in the package. The script is in
biopython/Bio/Restriction/Scripts. It will connect directly to the
rebase ftp server and download the last batch of emboss files. From a
DOS or Unix shell do the following :<br>
<pre>$ cd path_to_/Scripts<br>$ ls<br>ranacompiler.py rebase_update.py<br>$ ./rebase_update.py -m your_e_mail@my_address.com -p http://www.somewhere.com:8000<br><br>Please wait, trying to connect to Rebase<br><br><br>copying ftp://ftp.neb.com/pub/rebase/emboss_e.407<br>to /cvsroot/biopython/Bio/Restriction/Scripts/emboss_e.407<br>copying ftp://ftp.neb.com/pub/rebase/emboss_s.407<br>to /cvsroot/biopython/Bio/Restriction/Scripts/emboss_s.407<br>copying ftp://ftp.neb.com/pub/rebase/emboss_r.407<br>to /cvsroot/biopython/Bio/Restriction/Scripts/emboss_r.407<br><br></pre>
Some explanation are needed : <span style="font-family: monospace;">-m</span>
stands for e-mail, in order to connect to the ftp server you need to
provide a your e-mail address. So replace <span
style="font-family: monospace;">your_e_mail@your_address.com</span>
with your e-mail address. <span style="font-family: monospace;">-p</span>
is the switch to indicate to the script you are using a proxy. If you
use a ftp proxy enter its address and the connection port after the '<span
style="font-family: monospace;">:</span>'.<br>
<span style="font-family: monospace;"></span>
<h4><a class="mozTocH4" name="mozTocId49285"></a>6.2 Compiling a new
dictionary : the script ranacompiler.py<br>
</h4>
Once you have got a the last serie of emboss files you can compile a
new module containing the data necessary to create restriction enzyme.
You will need to get out of the python shell and open either a DOS
shell on windows, or your prefered Unix shell for the others.<br>
<br>
Note : if the emboss files are not present in the current directory or
if they are not up to date, <span style="font-family: monospace;">ranacompiler.py</span>
will invoke the script rebase_update. You will need to use the same
options as before (ie <span style="font-family: monospace;">-m</span>
and <span style="font-family: monospace;">-p</span>). See the previous
paragraph on <span style="font-family: monospace;">rebase_update.py</span>
for more details.<br>
<br>
For
simplicity let's assume we have put the emboss files in the same folder
as the files which contains the script <span
style="font-family: monospace;">ranacompiler.py</span>.<br>
<pre><br>$ cd path_to_/Scripts<br>$ ls<br>emboss_e.407 emboss_r.407 emboss_s.407 ranacompiler.py rebase_update.py<br><br></pre>
We will use the script <span style="font-family: monospace;">ranacompiler.py</span>.
You may have the change the mode of the file to make it executable :<br>
<pre>$ chmod '+x' ranacompiler.py<br></pre>
Now execute the script :<br>
<pre>$ python ranacompiler.py # or ./ranacompiler.py</pre>
You get normally the following message :<br>
<pre>$ ./ranacompiler.py<br><br> Using the files : emboss_e.407, emboss_r.407, emboss_s.407<br><br>WARNING : HaeIV cut twice with different overhang length each time.<br> Unable to deal with this behaviour.<br> This enzyme will not be included in the database. Sorry.<br> Checking : Anyway, HaeIV is not commercially available.<br><br><br>WARNING : TaqII has two different sites.<br><br>WARNING : It seems that AspCNI is both commercially available<br> and its characteristics are unknown.<br> This seems counter-intuitive.<br> There is certainly an error either in ranacompiler or<br> in this REBASE release.<br> The supplier is : New England Biolabs.<br><br>The new database contains 671 enzymes.<br><br>Writing the dictionary containing the new Restriction classes. OK.<br><br>Writing the dictionary containing the suppliers datas. OK.<br><br>Writing the dictionary containing the Restriction types. OK.<br><br><br> ******************************************************************************<br><br> Compilation of the new dictionary : OK.<br> Installation : No.<br><br> You will find the newly created 'Restriction_Dictionary.py' file<br> in the folder :<br><br> /cvsroot/biopython/Bio/Restriction/Scripts<br><br> Make a copy of 'Restriction_Dictionary.py' and place it with<br> the other Restriction libraries.<br><br> note :<br> This folder should be :<br><br> /usr/lib/python2.3/site-packages/Bio/Restriction<br><br><br> ******************************************************************************<br></pre>
The first line indicate which emboss files have been used for the
present compilation. You can safely ignore the warnings as long as the<span
style="font-family: monospace;"> compilation of the new
dictionary : OK.</span>
is present in the last part of the output. They are here for debugging
purpose. The number of enzymes in the new module is indicated as
well as a list of the dictionary which have been compiled. The last
part indicate that the module has been succesfully created but not
installed. To finish the update you must copy the file<span
style="font-family: monospace;">
/cvsroot/biopython/Bio/Restriction/Scripts/Restriction_Dictionary.py</span>
into the folder <span style="font-family: monospace;">/usr/lib/python2.3/site-packages/Bio/Restriction/</span>
as indicated by the script. Looking into the present folder, you will
see to new files : the newly created dictionary <span
style="font-family: monospace;">Restriction_Dictionary.py </span>and <span
style="font-family: monospace;">Restriction_Dictionary.old</span>
. This last file containing the old dictionary to which you can revert
in case anything the new file is corrupted (this should not happen
since the script is happy enough the new dictionary is good, but if
there is a problem it is always nice to know you can revert to the
previous setting without having to reinstall the whole thing.<br>
<pre>$ ls<br>emboss_e.407 ranacompiler.py* Restriction_Dictionary.py<br>emboss_r.407 rebase_update.py*<br>emboss_s.407 Restriction_Dictionary.old<br>$<br>$ # complete the installation by copying the new dictionary to the Bio/Restriction/ folder.<br>$ # You may have to become root to do this :<br>$<br>$ su -c "cp Restriction_Dictionary.py <span
style="font-family: monospace;">/usr/lib/python2.3/site-packages/Bio/Restriction/"<br>password :<br></span></pre>
Enter your password and that's it. If you whish, the script may install
the folder for you as well,
but you will have to run it as root if your normal user has no write
access to your python installation (and it should'nt). Use the command <span
style="font-family: monospace;">ranacompiler.py -i</span> or <span
style="font-family: monospace;">ranacompiler.py --install</span>.<br>
<pre>$ su -c "./ranacompiler.py -i"<br>password :<br><br> Using the files : emboss_e.407, emboss_r.407, emboss_s.407<br><br>WARNING : HaeIV cut twice with different overhang length each time.<br> Unable to deal with this behaviour.<br> This enzyme will not be included in the database. Sorry.<br> Checking : Anyway, HaeIV is not commercially available.<br><br><br>WARNING : TaqII has two different sites.<br><br>WARNING : It seems that AspCNI is both commercially available<br> and its characteristics are unknown.<br> This seems counter-intuitive.<br> There is certainly an error either in ranacompiler or<br> in this REBASE release.<br> The supplier is : New England Biolabs.<br><br>The new database contains 671 enzymes.<br><br>Writing the dictionary containing the new Restriction classes. OK.<br><br>Writing the dictionary containing the suppliers datas. OK.<br><br>Writing the dictionary containing the Restriction types. OK.<br><br><br> ******************************************************************************<br><br><br> Installing Restriction_Dictionary.py<br><br> The new file seems ok. Proceeding with the installation.<br><br> Everything ok. If you need it a version of the old<br> dictionary have been saved in the Updates folder under<br> the name Restriction_Dictionary.old.<br><br> ******************************************************************************</pre>
Much of the same really, but this time the module has directly been
installed with your other python modules, you don't need to do anything
more. If anything goes wrong (you have no write access to the
destination folder for example) the script will let you know it did not
perform the installation. It will however still save the new module in
the current directory :<br>
<pre>$ ./ranacompiler.py -i<br><br> Using the files : emboss_e.407, emboss_r.407, emboss_s.407<br><br>WARNING : HaeIV cut twice with different overhang length each time.<br> Unable to deal with this behaviour.<br> This enzyme will not be included in the database. Sorry.<br> Checking : Anyway, HaeIV is not commercially available.<br><br><br>WARNING : TaqII has two different sites.<br><br>WARNING : It seems that AspCNI is both commercially available<br> and its characteristics are unknown.<br> This seems counter-intuitive.<br> There is certainly an error either in ranacompiler or<br> in this REBASE release.<br> The supplier is : New England Biolabs.<br><br>The new database contains 671 enzymes.<br><br>Writing the dictionary containing the new Restriction classes. OK.<br><br>Writing the dictionary containing the suppliers datas. OK.<br><br>Writing the dictionary containing the Restriction types. OK.<br><br><br> ******************************************************************************<br><br><br> Installing Restriction_Dictionary.py<br><br> The new file seems ok. Proceeding with the installation.<br><br> ******************************************************************************<br><br><br> WARNING : Impossible to install the new dictionary.<br> Are you sure you have write permission to the folder :<br><br> /usr/lib/python2.3/site-packages/Bio/Restriction ?<br><br><br><br> ******************************************************************************<br><br> Compilation of the new dictionary : OK.<br> Installation : No.<br><br> You will find the newly created 'Restriction_Dictionary.py' file<br> in the folder :<br><br> /home/bssfs/cvsroot/biopython/Bio/Restriction/Scripts<br><br> Make a copy of 'Restriction_Dictionary.py' and place it with<br> the other Restriction libraries.<br><br> note :<br> This folder should be :<br><br> /usr/lib/python2.3/site-packages/Bio/Restriction<br><br><br> ******************************************************************************<br></pre>
As you can see the script is not very bright and will redo the
compilation each time it is invoked, no matter if a previous version of
the module is already present. <br>
<h4><a class="mozTocH4" name="mozTocId968583"></a>6.3 Subclassing
the class Analysis<br>
</h4>
As seen previously, you can modify some aspects of the Analysis output
interactively. However if you want to write your own Analysis class,
you may wish to provide others output facilities than is given in this
package. Depending on what you want to do you may get away with simply
changing the <span style="font-family: monospace;">make_format</span>
method of your derived class or you will need
to provide new methods. Rather than get into a long explanation, here
is the implementation of a rather useless Analysis class :<br>
<pre>>>> class UselessAnalysis(Analysis) :<br><br> def __init__(self, rb=RestrictionBatch(), seq=Seq(''), lin=True) :<br> """UselessAnalysis -> A class that waste your time"""<br> #<br> # Unless you want to do something more fancy all<br> # you need to do here is instantiate Analysis.<br> # Don't forget the self in __init__<br> #<br> Analysis.__init__(self, rb, seq, lin)<br><br> def make_format(self, cut=[], t='', nc=[], s='') :<br> """not funny"""<br> #<br> # Generally, you don't need to do anything else here<br> # This will tell to your new class to default to the <br> # _make_joke format.<br> #<br> return self._make_joke(cut, t, nc, s)<br><br> def print_as(self, what='joke') :<br> """Never know somebody might want to change the behaviour of<br> this class."""<br> #<br> # add your new option to print_as<br> #<br> if what == 'joke' :<br> self.make_format = self._make_joke<br> return<br> else :<br> #<br> # The other options will be treated as before<br> # <br> return Analysis.print_as(self, what)<br><br> def _make_joke(self, cut=[], title='', nc=[], s1='') :<br> """UA._make_joke(cut, t, nc, s) -> new analysis output"""<br> #<br> # starting your new method with '_make_'<br> # will give a hint to what it is suppose to do <br> # <br> # We will not process the non-cutting enzymes <br> # Their names are in nc<br> # s1 is the string printed before them <br> #<br> if not title :<br> title = '\nYou have guessed right the following enzymes :\n\n' <br> for name, sites in cut :<br> #<br> # cut contains :<br> # - the name of the enzymes which cut the sequence (name) <br> # - a list of the site positions (sites)<br> #<br> guess = raw_input("next enzyme is %s, Guess how many sites ?\n>>> "%name)<br> try :<br> guess = int(guess)<br> except :<br> guess = None<br> if guess == len(sites) :<br> print 'You did guess right. Good. Next.'<br> result = '%i site' % guess<br> if guess > 1 :<br> result += 's' <br> <br> #<br> # now we format the line. See the PrintFormat module<br> # for some examples <br> # PrintFormat.__section_list and _make_map are good start.<br> # <br> title=''.join((title, str(name).ljust(self.NameWidth),<br> ' : ', result, '.\n'))<br> print '\nNo more enzyme.'<br> return title <br> #<br> # I you want to print the non cutting enzymes use <br> # the following return instead of the previous one :<br> #<br> #return title + t + self._make_nocut_only(nc,s1)<br><br>>>> # You initiate and use it as before<br>>>> rb = RestrictionBatch([], ['A']) <br>>>> multi_site = Seq('AAA' + EcoRI.site +'G' + KpnI.site + EcoRV.site + 'CT' +\ <br>SmaI.site + 'GT' + FokI.site + 'GAAAGGGC' + EcoRI.site + 'ACGT', IUPACAmbiguousDNA())<br>>>><br>>>> b = UselessAnalysis(rb, multi_site)<br>>>> b.print_that() # Well, I let you discover if you haven't already guessed </pre>
<br>
Using this example, as a template you should now be able to subclass
Analysis as you wish. You will found more implementation details in the
module <span style="font-family: monospace;">Bio.Restriction.PrintFormat</span>
which contains the class providing all the <span
style="font-family: monospace;">_make_*</span> methods.<br>
<pre> </pre>
<h3><a class="mozTocH3" name="mozTocId114111"></a>7 Limitation
and caveat <br>
</h3>
You must be aware that Restriction is a fairly young package.
Particularly, the class Analysis is a quick and
dirty implementation based on the facilities furnished by the package.
Please check your
results and report any fault.<br>
<br>
On a more general basis, Restriction have some other limitations :<br>
<h4><a class="mozTocH4" name="mozTocId218594"></a>7.1 All DNA are non
methylated<br>
</h4>
No facility to work with methylated DNA has been implemented yet. As
far as the enzyme classes are concerned all DNA is non methylated DNA.
Implementation of methylation sensibility will certainly occur in the
future. But for now, if your sequence is methylated, you will have to
check if the site is methylated using other means. <br>
<h4><a class="mozTocH4" name="mozTocId790484"></a>7.2 No support for
star activity<br>
</h4>
As before no support has been yet implemented to find site
mis-recognised by enzymes under high salt concentration conditions, the
so-called star activity. This will be implemented as soon as I can get
a good source of information for that.<br>
<h4><a class="mozTocH4" name="mozTocId218334"></a>7.3 Safe to use with
degenerated DNA<br>
</h4>
It is safe to use degenerated DNA as input for the query. You will not
be flooded with meaningless results. But this come at a price : GAA<span
style="text-decoration: underline;">N</span>TC
will not be recognised as a potential EcoRI site for example, in fact
it will not
be recognised at all. Degenerated sequences will not be analysed. If
your sequence is not fully sequenced, you will certainly miss
restriction sites :<br>
<pre>>>> a = Seq('nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnGAATTCrrrrrrrrrrr', IUPACAmbiguousDNA())<br>>>> EcoRI.search(a)<br>[36]<br>>>> b = Seq('nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnGAAnTCrrrrrrrrrrr', IUPACAmbiguousDNA())<br>>>> EcoRI.search(b)<br>[]<br></pre>
<h4><a class="mozTocH4" name="mozTocId49392"></a>7.4 Non standard bases
in DNA are not
allowed<br>
</h4>
While you can use degenerated DNA, using non standard base alphabet
will make the enzymes choke, even if Bio.Seq.Seq accepts them. However,
space-like characters (' ', '\n', '\t', ...) and digit will be removed
but will not stop the enzyme analysing the sequence. You can use them
but the fragments produced by catalyse will have lost any formatting.
Catalyse try to keep the original case of the sequence (i.e lower case
sequences will generate lower case fragments, upper case sequences
upper case fragments), but mixed case will return upper case fragments :<br>
<pre>>>> c = Seq('xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxGAANTCrrrrrrrrrrr', IUPACAmbiguousDNA())<br>>>> EcoRI.search(c)<br><br>Traceback (most recent call last):<br> File "<pyshell#110>", line 1, in -toplevel-<br> EcoRI.search(b)<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 396, in search<br> cls.dna = FormatedSeq(dna, linear)<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 137, in __init__<br> self.format()<br> File "/usr/lib/python2.3/site-packages/Bio/Restriction/Restriction.py", line 153, in format<br> raise AlphabetError, " '%s' is not in the IUPAC alphabet" % s<br>AlphabetError: 'X' is not in the IUPAC alphabet<br>>>> d = Seq('1 nnnnn nnnnn nnnnn nnnnn nnnnn \n\<br>26 nnnnn nnnnG AATTC rrrrr rrrrr \n\<br>51 r', IUPACAmbiguousDNA())<br>>>> d<br>Seq('1 nnnnn nnnnn nnnnn nnnnn nnnnn \n26 nnnnn nnnnG AATTC rrrrr rrrrr \n51 r', IUPACAmbiguousDNA())<br>>>> EcoRI.search(d)<br>[36]<br>>>> EcoRI.catalyse(d)<br>(Seq('AATTCRRRRRRRRRRR', IUPACAmbiguousDNA()), Seq('NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNG', IUPACAmbiguousDNA()))<br>>>> e = Seq('nnnnGAATTCrr', IUPACAmbiguousDNA())<br>>>> f = Seq('NNNNGAATTCRR', IUPACAmbiguousDNA())<br>>>> g = Seq('nnnngaattcrr', IUPACAmbiguousDNA())<br>>>> EcoRI.catalyse(e)<br>(Seq('NNNNG', IUPACAmbiguousDNA()), Seq('AATTCRR', IUPACAmbiguousDNA()))<br>>>> EcoRI.catalyse(f)<br>(Seq('NNNNG', IUPACAmbiguousDNA()), Seq('AATTCRR', IUPACAmbiguousDNA()))<br>>>> EcoRI.catalyse(g)<br>(Seq('nnnng', IUPACAmbiguousDNA()), Seq('aattcrr', IUPACAmbiguousDNA()))<br></pre>
Not allowing other letters than IUPAC might seems drastic but this is
really to limit errors. It is not
totally fool proof but it does help. <br>
<br>
<h4><a class="mozTocH4" name="mozTocId395117"></a>7.5 Sites found at
the edge of linear
DNA might not be accessible in a real digestion<br>
</h4>
While sites clearly outsides a sequence will not be reported, nothing
has been done to try to determine if a restriction site at the end of a
linear sequence is valid :<br>
<pre>>>> d = Seq('GAATTCAAAAAAAAAAAAAAAAAAAAAAAAAAGGATG', IUPACAmbiguousDNA())<br>>>> FokI.site # site present<br>'GGATG'<br>>>> FokI.elucidate() # but cut outside the sequence <br>'GGATGNNNNNNNNN^NNNN_N'<br>>>> FokI.search(d) # therefore no site found<br>[]<br>>>> EcoRI.search(d)<br>[2] <br></pre>
EcoRI finds a site at position 2 even if it is highly unlikely that
EcoRI accepts to cut this site in a tube. It is generally considered
that at about 5 nucleotides must separate the site from the edge of the
sequence to be reasonably sure the enzyme will work correctly. This
"security margin" is variable from one enzyme to the other. In doubt
consult the documentation for the enzyme.<br>
<h4><a class="mozTocH4" name="mozTocId112206"></a>7.6 Restriction
reports cutting sites
not enzyme recognition sites<br>
</h4>
Some enzymes will cut twice each time they encounter a restriction
site. The enzymes in this package report both cut not the site. Other
software may only reports restriction sites. Therefore the output given
for some enzymes might seems to be the double when compared with the
results of these software. It is not a bug.<br>
<pre>>>> AloI.cut_twice()<br>True<br>>>> AloI.fst5 # first cut<br>-7<br>>>> AloI.scd5 # second cut <br>25<br>>>> AloI.site<br>'GAACNNNNNNTCC'<br>>>> b = Seq('AAAAAAAAAAA'+ AloI.site + 'AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA')<br>>>> b<br>Seq('AAAAAAAAAAAGAACNNNNNNTCCAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA', Alphabet())<br>>>> AloI.search(b) # one site, two cuts -> two positions<br>[5, 37]<br><br><br><br></pre>
<h3><a class="mozTocH3" name="mozTocId386540"></a>8 Annexe :
modifying dir() to use
with from Bio.Restriction import *<br>
</h3>
Having all the enzymes imported directly in the shell is useful when
working in an interactive shell (even if it is not recommended by the
purists). Here is a little hack to get some sanity back when using
dir() in those conditions :<br>
<pre>>>> # we will change the builtin dir() function to get ride of the enzyme names.<br>>>> import sys<br>>>> def dir(object=None) :<br> """dir([object]) -> list of string.<br><br> over-ride the built-in function to get some clarity."""<br> if object :<br> # we only want to modify dir(),<br> # so here we return the result of the builtin function.<br> return __builtins__.dir(object)<br> else :<br> # now the part we want to modify.<br> # All the enzymes are in a RestrictionBatch (we will talk about<br> # that later, for the moment simply believe me).<br> # So if we remove from the results of dir() everything which is<br> # in AllEnzymes we will get a much shorter list when we do dir()<br> #<br> # the current level is __main__ ie dir() is equivalent to<br> # ask what's in __main__ at the moment.<br> # we can't access __main__ directly.<br> # so we will use sys.modules['__main__'] to reach it.<br> # the following list comprehension remove from the result of<br> # dir() everything which is also present in AllEnzymes.<br> #<br> return [x for x in __builtins__.dir(sys.modules['__main__'])<br> if not x in AllEnzymes]<br><br> <br>>>> # now let's see if it works.<br>>>> dir()<br>['AllEnzymes', 'Analysis', 'CommOnly', 'NonComm', 'PrintFormat', 'RanaConfig',<br> 'Restriction', 'RestrictionBatch', 'Restriction_Dictionary', '__builtins__',<br> '__doc__', '__name__', 'dir', 'sys']<br>>>> # ok that's much better.<br>>>> # The enzymes are still there<br>>>> EcoRI.site<br>'GAATTC'<br><br><br></pre>
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