Data_Types.rst 10.1 KB
Newer Older
1
2
3
.. sectnum::
   :start: 4
   
Bertrand  NÉRON's avatar
Bertrand NÉRON committed
4
5
6
7
8
.. _Data_Types:

**********
Data Types
**********
9
10
11
12
13
14
15
16
17
18
19
20
21
22

Exercices
=========

Exercise
--------

Assume that we execute the following assignment statements: ::

   width = 17
   height = 12.0
   delimiter ='.'

For each of the following expressions, write the value of the expression and the type (of the value of
23
the expression) and explain. 
24

25
26
27
28
 #. width / 2
 #. width / 2.0
 #. height / 3
 #. 1 + 2 * 5
29
30
31
32
33
34
35
36
37
38
39
40
41
42
   
Use the Python interpreter to check your answers. ::

   >>> width = 17
   >>> height = 12.0
   >>> delimiter ='.'
   >>> 
   >>> width / 2
   8
   >>> # both operands are integer so python done an euclidian division and threw out the remainder
   >>> width / 2.0
   8.5
   >>> height / 3
   4.0
43
44
   >>> # one of the operand is a float (2.0 or height) then python pyhton perform a float division but keep in mind that float numbers are approximation.
   >>> # if you need precision you need to use Decimal. But operations on Decimal are slow and float offer quite enough precision
45
46
   >>> # so we use decimal only if wee need great precision
   >>> # Euclidian division
47
   >>> 2 // 3
48
49
   0
   >>> # float division
50
   >>> 2 / 3
51
   0.6666666666666666
52

53
54
55
56
57


Exercise
--------

58
Write a function which take a radius as input and return the volume of a sphere:
59

60
61
62
63
64
65
66
67
The volume of a sphere with radius r is 4/3 πr\ :sup:`3`. 

What is the volume of a sphere with radius 5?

**Hint**: π is in math module, so to access it you need to import the math module 
Place the ``import`` statement at the top fo your file.
after that, you can use ``math.pi`` everywhere in the file like this::
      
68
      >>> import math
69
70
71
      >>>
      >>> #do what you need to do
      >>> math.pi #use math.pi
72

73
74
75
76
77
78
79
80
81
82
83
.. literalinclude:: _static/code/vol_of_sphere.py
   :linenos:
   :language: python

::

   python -i volume_of_sphere.py 
   >>> vol_of_sphere(5)
   523.5987755982989
   
:download:`vol_of_sphere.py <_static/code/vol_of_sphere.py>` .      
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177

Exercise
--------

Draw what happen in memory when the following statements are executed: ::

   i = 12
   i += 2
   
.. figure:: _static/figs/augmented_assignment_int.png
   :width: 400px
   :alt: set
   :figclass: align-center
   
::      

   >>> i = 12
   >>> id(i)
   33157200
   >>> i += 2
   >>> id(i)
   33157152


and ::

   s = 'gaa'
   s = s + 'ttc' 
   
.. figure:: _static/figs/augmented_assignment_string.png
   :width: 400px
   :alt: set
   :figclass: align-center   

::   

   >>> s = 'gaa'
   >>> id(s)
   139950507582368
   >>> s = s+ 'ttc'
   >>> s
   'gaattc'
   >>> id(s)
   139950571818896
   
when an augmented assignment operator is used on an immutable object is that 
 
#. the operation is performed, 
#. and an object holding the result is created  
#. and then the target object reference is re-bound to refer to the
   result object rather than the object it referred to before. 

So, in the preceding case when the statement ``i += 2`` is encountered, Python computes 1 + 2 , stores
the result in a new int object, and then rebinds ``i`` to refer to this new int . And
if the original object a was referring to has no more object references referring
to it, it will be scheduled for garbage collection. The same mechanism is done with all immutable object included strings.
  
Exercise
--------

how to obtain a new sequence which is the 10 times repetition of the this motif : "AGGTCGACCAGATTANTCCG"::
   >>> s = "AGGTCGACCAGATTANTCCG"
   >>> s10 = s * 10

Exercise
--------

create a representation in fasta format of following sequence :

.. note::
   A sequence in FASTA format begins with a single-line description, followed by lines of sequence data. 
   The description line is distinguished from the sequence data by a greater-than (">") symbol in the first column. 
   The word following the ">" symbol is the identifier of the sequence, and the rest of the line is the description (optional). 
   There should be no space between the ">" and the first letter of the identifier. 
   The sequence ends if another line starting with a ">" appears; this indicates the start of another sequence. 

::

   id = "sp|P60568|IL2_HUMAN"

   comment = "Interleukin-2 OS=Homo sapiens GN=IL2 PE=1 SV=1"

   sequence = """MYRMQLLSCIALSLALVTNSAPTSSSTKKTQLQLEHLLLDLQMILNGINNYKNPKLTRML
   TFKFYMPKKATELKHLQCLEEELKPLEEVLNLAQSKNFHLRPRDLISNINVIVLELKGSE
   TTFMCEYADETATIVEFLNRWITFCQSIISTLT"""

   >>> s = id + comment + '\n' + sequence
   or
   >>> s = "{id} {comment} \n{sequence}".format(id= id, comment = comment, sequence = sequence)   
   
   
Exercise
--------

178
179
For the following exercise use the python file :download:`sv40 in fasta <_static/code/sv40_file.py>` which is a python file with the sequence of sv40 in fasta format
already embeded, and use python -i sv40_file.py to work.
180
181
182
183
184

how long is the sv40 in bp? 
Hint : the fasta header is 61bp long.
(http://www.ncbi.nlm.nih.gov/nuccore/J02400.1)

185
186
187
188
189
190
191
pseudocode

write a function ``fasta_to_one_line`` that return a sequence as a string
without header or any non sequence characters

pseudocode:

192
|   *function fasta_to_one_line(seq)*
193
194
195
196
197
198
199
200
201
202
|      *header_end_at <- find the first return line character*
|      *raw_seq <- remove header from sequence*
|      *raw_seq <- remove non sequence chars*
|      *return raw_seq*


.. literalinclude:: _static/code/fasta_to_one_line.py
   :linenos:
   :language: python

203
   
204
205
206
207
208
:download:`fasta_to_one_line.py <_static/code/fasta_to_one_line.py>` . 

::

   python
209
   >>> import sv40_file
210
211
   >>> import fasta_to_one_line
   >>>
212
213
   >>> sv40_seq = fasta_to_one_line(sv40_file.sv40_fasta) 
   >>> print len(sv40_seq)
214
215
216
   5243

Is that the following enzymes: 
217

218
219
220
221
* BamHI (ggatcc), 
* EcorI (gaattc), 
* HindIII (aagctt), 
* SmaI (cccggg) 
222
223

have recogition sites in sv40 (just answer by True or False)? ::
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250

   >>> "ggatcc".upper() in sv40_sequence
   True
   >>> "gaattc".upper() in sv40_sequence
   True
   >>> "aagctt".upper() in sv40_sequence
   True
   >>> "cccggg".upper() in sv40_sequence
   False

for the enzymes which have a recognition site can you give their positions? ::

   >>> sv40_sequence = sv40_sequence.lower()
   >>> sv40_sequence.find("ggatcc")
   2532
   >>> # remind the string are numbered from 0
   >>> 2532 + 1 = 2533 
   >>> # the recognition motif of BamHI start at 2533
   >>> sv40_sequence.find("gaattc")
   1781
   >>> # EcorI -> 1782
   >>> sv40_sequence.find("aagctt")
   1045
   >>> # HindIII -> 1046
   
is there only one site in sv40 per enzyme? 

251
252
253
254
The ``find`` method give the index of the first occurrence or -1 if the substring is not found.
So we can not determine the occurrences of a site only with the find method.
We can know how many sites are present with the ``count`` method.
We will see how to determine the site of all occurrences when we learn looping and conditions.
255
256
257
258
259
260
261


Exercise
--------

We want to perform a PCR on sv40, can you give the length and the sequence of the amplicon?

262
263
264
Write a function which have 3 parameters ``sequence``, ``primer_1`` and ``primer_2``

* *We consider only the cases where primer_1 and primer_2 are present in sequence* 
Bertrand  NÉRON's avatar
Bertrand NÉRON committed
265
* *to simplify the exercise, the 2 primers can be read directly on the sv40 sequence.*
266
267
268
269

test you algorithm with the following primers 

| primer_1 : 5' CGGGACTATGGTTGCTGACT 3'
Bertrand  NÉRON's avatar
Bertrand NÉRON committed
270
| primer_2 : 5' TCTTTCCGCCTCAGAAGGTA 3'
271
272
273
274
275
276
277
278
279
280
281
282
283

Write the pseudocode before to implement it.

| *function amplicon_len(sequence primer_1, primer_2)*
|      *pos_1 <- find position of primer_1 in sequence*
|      *pos_2 <- find position of primer_2 in sequence*
|      *amplicon length <- pos_2 + length(primer_2) - pos_1*
|      *return amplicon length* 


.. literalinclude:: _static/code/amplicon_len.py
   :linenos:
   :language: python
284
285
286

::

287
288
289
290
291
   >>> import sv40 
   >>> import fasta_to_one_line
   >>> 
   >>> sequence = fasta_to_one_line(sv40)
   >>> print amplicon_len(sequence, first_primer, second_primer )
292
   199
293
294
295
   
:download:`amplicon_len.py <_static/code/amplicon_len.py>` . 

296
297
298
299
300
301
302
303
304
305
306

Exercise
--------

reverse the following sequence "TACCTTCTGAGGCGGAAAGA" (don't compute the complement): ::

   >>> "TACCTTCTGAGGCGGAAAGA"[::-1]
   or 
   >>> s = "TACCTTCTGAGGCGGAAAGA"
   >>> l = list(s) 
   # take care reverse() reverse a list in place (the method do a side effect and return None ) 
Bertrand  NÉRON's avatar
Bertrand NÉRON committed
307
   # so if you don't have a object reference on the list you cannot get the reversed list!
308
309
310
311
312
313
314
315
316
317
318
319
   >>> l.reverse()
   >>> print l
   >>> ''.join(l)
   or 
   >>> rev_s  = reversed(s)
   ''.join(rev_s)
 
 The most efficient way to reverse a string or a list is the way using the slice. 

Exercise
--------

320
321
322
| The il2_human contains 4 cysteins (C) in positions 9, 78, 125, 145. 
| We want to generate the sequence of a mutatnt were the cysteins 78 and 125 are replaced by serins (S)
| Write the pseudocode, before to propose an implementation:
323

324
We have to take care of the string numbered vs sequence numbered:
325
326
327
328
329
330
331

| C in seq -> in string
|     9 -> 8
|    78 -> 77
|   125 -> 124
|   145 -> 144

332
333
334
335
336
337
338
339
340
341
| *generate 3 slices from the il2_human*
| *head <- from the begining and cut between the first cytein and the second* 
| *body <- include  the 2nd and 3rd cystein*
| *tail <- cut after the 3rd cystein until the end* 
| *replace body cystein by serin* 
| *make new sequence with head body_mutate tail*
  
il2_human = 
'MYRMQLLSCIALSLALVTNSAPTSSSTKKTQLQLEHLLLDLQMILNGINNYKNPKLTRMLTFKFYMPKKATELKHLQCLEEELKPLEEVLNLAQSKNFHLRPRDLISNINVIVLELKGSETTFMCEYADETATIVEFLNRWITFCQSIISTLT'
  
342
343
344
345
346
347
348
349
350
351
352
353
  
::

   head = il2_human[:77]
   body = il2_human[77:125]
   tail = il2_human[126:]
   body_mutate = body.replace('C', 'S')
   il2_mutate = head + body_mutate + tail

Exercise
--------

354
355
Write a function 

Bertrand  NÉRON's avatar
Bertrand NÉRON committed
356
* which take a sequence as parameter
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
* compute the GC%
* and return it
* display the results readable for human as a micro report like this:
  'the sv40 is 5243 bp length and have 40.80% gc' 
  
use sv40 sequence to test your function.

.. literalinclude:: _static/code/gc_percent.py
   :linenos:
   :language: python

::

   >>> import sv40 
   >>> import fasta_to_one_line
   >>> import gc_percent
   >>> 
   >>> sequence = fasta_to_one_line(sv40)
   >>> gc_pc = gc_percent(sequence)
376
   >>> report = "the sv40 is {0} bp length and have {1:.2%} gc".format(len(sequence), gc_pc)
377
378
379
380
   >>> print report
   'the sv40 is 5243 bp length and have 40.80% gc'
   
:download:`gc_percent.py <_static/code/gc_percent.py>` .