ComGen Course

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Contents

2011 Spring

Textbook
Presentation by students
  • One chapter per each student
  • No exam (Project submission)
(Temporary) Schedule 
Chapter	Name	Pages	Presentation	Due date
python  HSRoh   Introduction 3/15/11
1	SJKim	21	03/22/11	03/18/11
2	JHLee	16	03/29/11	03/25/11
3	BHKim	23	04/05/11	03/28/11
4	JISong	17	04/12/11	04/08/11
Midterm (4/19/11) - no exam
5	HJKim	18	04/26/11	04/22/11			
6	JWLee	14	05/03/11	04/29/11
7	TBA	18	05/10/11	05/06/11
5/10/11 (Budda's birthday)
8	TBA	12	05/24/11	05/20/11
9	BHKim           05/31/11	05/27/11
10	TBA	21	06/07/11	06/03/11
Final			Project

Software

Python
about Python
Introduction to Programming using Python
Installing Python & related Modules (Windows & Linux only)
  • Python(x,y)-2.6.5.6 (Mar 2011) - Free scientific and engineering development software download & install
including almost every very useful scientific modules (Numpy, Scipy...)
Biopython Tutorial & Cookbook
Tutorials
Eric Talevich - Check his presentation files
Slide #1
Slide #2

Chapters

Introduction to Python Programming
노한성 발표자료 3-15-2011

Chapter 1

Chaos Game Representation

Exercise#1

Download a genome sequence & do basic statistical analysis
GC-content?
Solution = GC content of NC_01415 is '??? %'
Code 
>>> from Bio import Entrez, SeqIO
>>> Entrez.mail = 'your@email.address'
>>> handle = Entrez.efetch(db="nucleotide",id="NC_001416",rettype="fasta")
>>> record = SeqIO.read(handle,"fasta")
>>> print record
ID: gi|9626243|ref|NC_001416.1|
Name: gi|9626243|ref|NC_001416.1|
Description: gi|9626243|ref|NC_001416.1| Enterobacteria phage lambda, complete genome
Number of features: 0
Seq('GGGCGGCGACCTCGCGGGTTTTCGCTATTTATGAAAATTTTCCGGTTTAAGGCG...ACG', SingleLetterAlphabet())
>>> print len(record)
48502
>>> record
SeqRecord(seq=Seq('GGGCGGCGACCTCGCGGGTTTTCGCTATTTATGAAAATTTTCCGGTTTAAGGCG...ACG', SingleLetterAlphabet()), id='gi|9626243|ref|NC_001416.1|', name='gi|9626243|ref|NC_001416.1|', description='gi|9626243|ref|NC_001416.1| Enterobacteria phage lambda, complete genome', dbxrefs=[])
>>> record.seq
Seq('GGGCGGCGACCTCGCGGGTTTTCGCTATTTATGAAAATTTTCCGGTTTAAGGCG...ACG', SingleLetterAlphabet())
>>> from Bio.SeqUtils import GC
>>> GC(record.seq)
49.857737825244321
GC-values of windowsize 500


>>> x = record.seq
>>> windowsize = 500
>>> gc_values = [ GC(x[i:(i+499)] for i in range(1,len(x)-windowsize+1) ]
>>> import pylab
>>> pylab.plot(gc_values)
>>> pylab.title("GC% 500 bp window size")
>>> pylab.xlabel("Nucleotide positions")
>>> pylab.ylabel("GC%")
>>> pylab.show()

Exercise#2

Basic Statistical Analysis 
>>> from Bio import Entrez, SeqIO
>>> handle = Entrez.efetch(db="nucleotide",id="NC_001807",rettype="fasta")
>>> record1 = SeqIO.read(handle,"fasta")
>>> handle = Entrez.efetch(db="nucleotide",id="NC_001643",rettype="fasta")
>>> record2 = SeqIO.read(handle,"fasta")
>>> from Bio.SeqUtils import GC
>>> GC(record1.seq)
44.487357431657713
>>> GC(record2.seq)
43.687326325963511
>>> len(record2.seq)
16554
>>> len(record1.seq)
16571

Exercise#3

Most frequent word 
>>> from Bio import Entrez, SeqIO
>>> handle = Entrez.efetch(db="nucleotide",id="NC_001665",rettype="fasta")
>>> ratMT = SeqIO.read(handle,"fasta")
>>> base = [ ratMT.seq[i] for i in range(0,len(ratMT.seq))]
>>> a = base.count('A')
>>> g = base.count('G')
>>> c = base.count('C')
>>> t = base.count('T')
>>> di = [ str(ratMT.seq[i:(i+2)]) for i in range(0,len(ratMT.seq)-1) ]
>>> aa = di.count('AA')
>>> aa
1892
>>> a
5544

Chapter 2

related topics
  1. GeneSweep result
  2. Type I & Type II errors
  3. Statitical power

Exercise

  1. Find all ORFs in Human, Chimp and Mouse mtDNA
  2. Repeat the ORF search on randomized mtDNA. The longest ORF in the randomized sequence?
  3. Find ORFs in H. influenzae
Exercise#1 Finding ORFs
>>> han1 = Entrez.efetch(db="nucleotide",id="NC_001807",rettype="fasta")
>>> hum = SeqIO.read(han1,"fasta")
>>> from Bio.Seq import Seq
>>> orf = hum.seq.translate(table="Vertebrate Mitochondrial")
>>> orf.count("*")
326
From Eric Talevich's presentation 
# define function 1 - translate a given sequences in all 6 frames
def translate_six_frames(seq, table=1):
    rev = seq.reverse_complement()
    for i in range(3):
        yield seq[i:].translate(table)
        yield rev[i:].translate(table)



# define function 2 - translate given sequences in 6 reading frames
# & return ORFs, min_prot_len = 'k'
def translate_orfs(sequences, min_prot_len=60):
    for frame in translate_six_frames(seq):
        for prot in frame.split('*'):
            if len(prot) >= min_prot_len:
                yield prot

# actual procedure
from Bio import SeqIO
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq

seq = 
proteins = translate_orfs(seq) 
seqrecords = (SeqRecord(seq,id='orf'+str(i))
           for i, seq in enumerate(proteins))
Exercise#2 Using randomized sequences
>>> import random
>>> nuc_list = list(hum.seq)
>>> random.shuffle(nuc_list)
Exercise#3
see, Excercis #1

Chapter 3

Exersize#1

Chapter 4

Exercise#1

Chapter 5

Exercise#1

  1. Which of the modern elephants seems to be more closely related to mammoths? Hint: make a global alignment and calculate the genetic distance between them
  2. 12S rRNA sequence of Saber-Tooth Tiger can tell which of modern felines is most closest one.
  3. Genetic distance between blue-whale, hippo and cow 
8 : from Bio import Entrez, SeqIO
9 : h1 = Entrez.efetch(db="nucleotide",id="NC_001601",rettype="fasta")
10: h2 = Entrez.efetch(db="nucleotide",id="NC_000889",rettype="fasta")
11: h3 = Entrez.efetch(db="nucleotide",id="NC_006853",rettype="fasta")
12: blue = SeqIO.read(h1,"fasta")
13: hipp = SeqIO.read(h2,"fasta")
14: cow = SeqIO.read(h3,"fasta")
19: seqs = [blue, hipp, cow]
20: h4 = open("seq.fasta","w")
21: SeqIO.write(seqs,h4,"fasta")
22: h4.close()

     Whale  Hippo Cow 
Whale 0     
Hippo 0.222 
Cow   0.226 0.226

Chapter 6

Chapter 7

Chapter 8

Chapter 9

A Thinking Chair

Links

Programming

Languages

Packages

Previous years

2009 Schedule

Chapter Assign Pages	Presentation    Due date
1	이은혜	21	03/19/09	03/12/09
2	박애경	16	03/26/09	03/21/09
3	고혁진	23	04/02/09	03/26/09
4	장은혁	17	04/07/09	04/02/09
5	이예림	18	04/16/09	04/07/09
6	김소현	14	04/23/09	04/16/09
7	정진아	18	05/14/09	04/23/09
8	김윤식	12	05/21/09	04/30/09
9	김윤식	18	06/04/09	05/07/09
10	김윤식	21	06/11/09	05/14/09
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