Commit 150ca035 authored by Bertrand  NÉRON's avatar Bertrand NÉRON
Browse files

add exercises with solutions

parent 3d5f313a
......@@ -38,9 +38,21 @@ The fibonacci suite can be defined as following:
a = b
b = new_number
We will see another way more elegant to implement the fibonacci suite in next chapter.
We will see another way more elegant to implement the fibonacci suite in :ref:`Advance Programming Techniques` section.
Exercise
--------
display the largest element in list (containing float or integer only)?::
l = [1,2,3,4,58,9]
for i in l:
highest = l[0]
if i > highest:
highest = i
print i
Exercise
--------
......
......@@ -3,3 +3,52 @@
******************************
Creating and Calling Functions
******************************
Exercises
=========
Exercice
--------
Use the code of the exetrcise 4.5.7 on the kmer. Make a function which compute all kmer of a given lenght
in a sequence.
Exercise
--------
Write a function translate taht have a nucleic sequence as parameter, and return the translate sequence.
We give you a genetic code : ::
code = { 'ttt': 'F', 'tct': 'S', 'tat': 'Y', 'tgt': 'C',
'ttc': 'F', 'tcc': 'S', 'tac': 'Y', 'tgc': 'C',
'tta': 'L', 'tca': 'S', 'taa': '*', 'tga': '*',
'ttg': 'L', 'tcg': 'S', 'tag': '*', 'tgg': 'W',
'ctt': 'L', 'cct': 'P', 'cat': 'H', 'cgt': 'R',
'ctc': 'L', 'ccc': 'P', 'cac': 'H', 'cgc': 'R',
'cta': 'L', 'cca': 'P', 'caa': 'Q', 'cga': 'R',
'ctg': 'L', 'ccg': 'P', 'cag': 'Q', 'cgg': 'R',
'att': 'I', 'act': 'T', 'aat': 'N', 'agt': 'S',
'atc': 'I', 'acc': 'T', 'aac': 'N', 'agc': 'S',
'ata': 'I', 'aca': 'T', 'aaa': 'K', 'aga': 'R',
'atg': 'M', 'acg': 'T', 'aag': 'K', 'agg': 'R',
'gtt': 'V', 'gct': 'A', 'gat': 'D', 'ggt': 'G',
'gtc': 'V', 'gcc': 'A', 'gac': 'D', 'ggc': 'G',
'gta': 'V', 'gca': 'A', 'gaa': 'E', 'gga': 'G',
'gtg': 'V', 'gcg': 'A', 'gag': 'E', 'ggg': 'G'
}
bonus
"""""
This function have to take the phase as parameter
bonus
"""""
This function can take genetique code as default parameter
......@@ -3,3 +3,92 @@
************************************
Variables, Expression and statements
************************************
Exercises
=========
Exercise
--------
Write a function which take the path of file as parameter
and display it's content on the screen.
We wait same behavior as the shell *cat* command. ::
import sys
import os
def cat(path):
if not os.path.exists(path):
sys.exit("no such file: {0}".format(path)
with open(path, 'r') as infile:
for line in infile:
print line
Exercise
--------
Write a function which take the path of a file in rebase format
and return in a dictionnary the collection of the enzyme contains in the file.
The sequence of the binding site must be cleaned up.
:download:`rebase_light.txt <_static/data/rebase_light.txt>` .
Exercise
--------
write a function which take the path of a fasta file
and return a data structure of your choice that allow to stock
the id of the sequence and the sequence itself.
:download:`seq.fasta <_static/data/seq.fasta>` .
solution 1
""""""""""
.. literalinclude:: _static/code/fasta_reader.py
:linenos:
:language: python
:download:`fasta_reader.py <_static/code/fasta_reader.py>` .
solution 2
""""""""""
.. literalinclude:: _static/code/fasta_iterator.py
:linenos:
:language: python
:download:`fasta_iterator.py <_static/code/fasta_iterator.py>` .
The second version is an iterator. Thus it retrun sequence by sequence the advantage of this version.
If the file contains lot of sequences you have not to load all the file in memory.
You can call this function and put in in a loop or call next. work with the sequence and pass to the next sequence on so on.
for instance : ::
for seq in fasta_iter('my_fast_file.fasta'):
print seq
Exercise
--------
we ran a blast with the folowing command *blastall -p blastp -d uniprot_sprot -i query_seq.fasta -e 1e-05 -m 8 -o blast2.txt*
-m 8 is the tabular output. So each fields is separate to the following by a '\t'
The fields are: query id, database sequence (subject) id, percent identity, alignment length, number of mismatches, number of gap openings,
query start, query end, subject start, subject end, Expect value, HSP bit score.
:download:`blast2.txt <_static/data/blast2.txt>` .
| parse the file
| sort the hits by their *percent identity* in the descending order.
| write the results in a new file.
(adapted from *managing your biological data with python* p138) ::
.. literalinclude:: _static/code/parse_blast_output.py
:linenos:
:language: python
:download:`parse_blast_output.py <_static/code/parse_blast_output.txt>` .
\ No newline at end of file
from collections import namedtuple
from itertools import groupby
Sequence = namedtuple("Sequence", "id comment sequence")
def fasta_iter(fasta_path):
"""
:param fasta_file: the file containing all input sequences in fasta format.
:type fasta_file: file object
:author: http://biostar.stackexchange.com/users/36/brentp
:return: for a given fasta file, it returns an iterator which yields tuples
(string id, string comment, int sequence length)
:rtype: iterator
"""
with open(fasta_path) as fasta_file:
# ditch the boolean (x[0]) and just keep the header or sequence since
# we know they alternate.
group = (x[1] for x in groupby(fasta_file , lambda line: line[0] == ">"))
for header in group:
# drop the ">"
header = header.next()[1:].strip()
header = header.split()
_id = header[0]
comment = ' '.join(header[1:])
seq = ''.join(s.strip() for s in group.next())
yield Sequence(_id, comment, seq)
#using exanple:
#f = fasta_iter('seq.fasta')
#f.next()
#or
# for seq in fasta_iter('seq.fasta'):
# do something with seq
\ No newline at end of file
from collections import namedtuple
Sequence = namedtuple("Sequence", "id comment sequence")
def fasta_reader(fasta_path):
with open(fasta_path, 'r') as fasta_infile:
id = ''
comment = ''
sequence = ''
in_sequence = False
for line in fasta_infile:
if line.startswith('>'):
header = line.split()
id = header[0]
comment = ' '.join(header[1:])
in_sequence = True
elif in_sequence:
sequence += line.strip()
else:
continue
return Sequence(id , comment, sequence)
\ No newline at end of file
from operator import itemgetter
def parse_blast_output(input_file, output_file):
with open(input_file, 'r') as infile:
table = []
for line in infile:
print i
col = line.split('\t')
try:
col[2] = float(col[2])
except ValueError as err:
raise RuntimeError("error in parsing {} : {}".format(input_file, err))
col[-1] = col[-1][:-1]
table.append(col)
#from this point the input_file is closed
table_sorted = sorted(table, key = itemgetter(2), reverse = True)
# alternative
# table_sorted = sorted(table, key = lambda x : x[2], reversed = True)
with open(output_file, 'w') as output:
for row in table_sorted:
row = [str(x) for x in row]
output.write("\t".join(row) + "\n")
......@@ -10,10 +10,13 @@ Contents:
.. toctree::
:maxdepth: 2
:numbered:
Introduction
Variables
Data_Types
Collection_Data_Types
Logical_Operations
Control_Flow_Statements
Creating_and_Calling_Functions
Modules_and_Packages
......
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