GS559: Introduction to Statistical and Computational Genomics (Winter 2014)
Instructors:
Jim Thomas, jht@uw.edu
Elhanan Borenstein, elbo@uw.edu
Schedule: Tues. Thurs, 3:30-4:50 (first class Jan. 7, last class Mar. 13), Hitchcock 220.
News:
» The final exam will take place in class, Thursday, March 13 (last class of the quarter). It will have two parts: The first will focus on the bioinformatics topics covered in class and the second on programming. You are allowed to use any static resource (i.e., books, notes).
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Assignments:
You are welcome to talk to classmates about principles for solving problems, but do NOT solve specific problems together. In many ways, the problem solving is where you will learn the most for this class, especially the programming.
All problem sets are due by the start of class on
the date listed. Grades will come 80% from problem sets and 20% from one final exam. There will be no mid-term exams.
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Test/Demo Files
The following files are used in some of the in-class exercises and demos.
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Lectures and Reading: |
Lecture # | Lecture Topic | Programming Topic | Reading |
1 |
Overview of course. Introduction to sequence comparison. BLAST, alignment scoring | PDF |
Introduction to Python. Interpreter, objects, types, variables, command line | PDF |
[1, 2] |
2 |
Sequence alignment - dynamic programming | PDF |
Strings | PDF |
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3 |
Sequence alignment - local alignment | PDF |
Numbers, lists, tuples | PDF |
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4 |
Sequence alignment - protein score matrices | PDF |
File input-ouput, if-then-else | PDF |
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5 |
Sequence alignment - signficance of similarity scores | PDF |
For loops | PDF |
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6 |
Signficance of similarity scores continued | PDF |
While loops | PDF |
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7 |
Whole genome alignments | PDF |
Loops and efficient code | PDF |
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8 |
Sequence trees - distance trees | PDF |
Dictionaries (hash maps) | PDF |
[3] |
9 |
Parsimony | PDF |
Functions | PDF |
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10 |
Small parsimony | PDF |
More on functions, modules | PDF |
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11 |
Gene ontology and functional enrichment | PDF |
Functions as arguments, sorting | PDF |
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12 |
Gene set enrichment analysis | PDF |
Classes and objects | PDF |
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13 |
Ab initio gene prediction | PDF |
Exception Handling | PDF |
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14 |
Gene expression: Clustring | PDF |
More on classes and objects | PDF |
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15 |
Gene expression: K-mean clustring | PDF |
Regular expressions | PDF |
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16 |
Biological networks; Dijkstra algorithm | PDF |
More regular expressions | PDF |
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17 |
Degree distribution and network motifs | PDF |
More on classes, Biopython | PDF |
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18 |
Recursion | PDF |
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19 |
In-class project | PDF |
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20 |
Final Exam |
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References:
Electronic access to journals is generally free from on-campus computers. For off-campus access, follow the "[offcampus]" links or look at the library "proxy server" instructions.
- Noble, WS, "A quick guide to organizing computational biology projects." PLoS Comput. Biol. 5 (2009) e1000424. Pmid: 19649301 [Offcampus]
- Dudley, JT and Butte, AJ, "A quick guide for developing effective bioinformatics programming skills." PLoS Comput. Biol. 5 (2009) e1000589. Pmid: 20041221 [Offcampus]
- How dictionaries work (aka hash tables or hash maps)
- Subramanian et al., "Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles"PNAS102(43) (2005)
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Python Resources:
General
Regular Expressions
"RegExPal" (For Javascript rather than Python, but similar and quite handy. Try it!)
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Biopython
Python Books
Learning Python by Mark Lutz. O'Reilly (Very comprehensive. Much is accessible to beginners.)
Dive Into Python 3 by Mark Pilgrim. (Another online book. Based on Python 3, so some differences, and more advanced, but also free.)
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Bioinformatics Books
» Biological sequence analysis: probabilistic models of proteins and nucleic acids, R. Durbin, S. Eddy, A. Krogh, and G. Mitchison, Cambridge. (Excellent reference, classics)
» Inferring Phylogenies, Joseph Felsenstein, Sinauer, 2004. (Excellent reference on this topic.)
» Introduction to Computational Genomics: A Case Studies Approach, Cristianini, Nello & Hahn, Matthew, Cambridge, 2007.
» An Introduction to Bioinformatics Algorithms, Neil C. Jones & Pavel A. Pevzner, 2004.
» Bioinformatics: Sequence and Genome Analysis, David W. Mount, Cold Spring Harbor Laboratory Press.
» Python for Bioinformatics, Sebastian Bassi, CRC Press, 2010. (A little too advanced as a progamming book for beginners, but fine now that you're experienced.)
» Python for Bioinformatics, Jason Kinser, Jones and Bartlett, 2009. (Ditto.)
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James H. Thomas
Department of Genome Sciences
University of Washington
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Elhanan Borenstein
Departments of Genome Sciences
University of Washington
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