Introduction to Statistical and Computational GenomicsGENOME 559
Department of Genome Sciences
University of Washington
Rudiments of statistical and computational genomics. Emphasis on basic probability and statistics, introduction to computer programming and relevant web databases. This course is intended to introduce students with non-computer science backgrounds to the major concepts of programming and statistics.
- William Stafford Noble
- Brian Beliveau
- Teaching assistant: Gesine Cauer, email@example.com
Please click on the links above for email addresses and office locations.
Meeting times and locations
- Classes: Monday and Wednesday, 10:30 - 11:50 am, online
- Office hours: Wednesday, 2:00 - 3:00 pm, Friday, 12:00 - 1:000 pm
Substantial background in molecular and cellular biology, genetics, biochemistry, or related disciplines.
Readings for the Python parts of the class will be assigned from the free online textbook Think Python.
- Late homework will be accepted, but penalized. Specifically, each assignment is worth 100 points, from which 10 points will be deducted for each day (or fraction thereof) that you turn it in late. The maximum deduction for being late is 60 points (even if you are more than 6 days late).
- You are welcome to talk to classmates about principles for solving problems, but please do not share code or solve specific problems together. The problem solving is where you will learn the most for this class, especially the programming.
There will be an open book final exam on the last day of class.
Grades will come 80% from problem sets and 20% from one final exam. There will be no mid-term exam. The final course grade is computed using the procedure described here.
- The course home page can be found at http://noble.gs.washington.edu/~noble/genome559.
- A Canvas page is at https://canvas.uw.edu/courses/1430304.
Date Lecture Topic Programming Topic Reading Homework
Wed Sep 30 Course overview. Intro to sequence comparison Introduction to Python Chapters 1-2 Mon Oct 5 Sequence comparison — dynamic programming Strings Chapter 8 Homework 1 Wed Oct 7 Sequence comparison — traceback Numbers, lists and tuples Chapters 10, 12 Mon Oct 12 Sequence comparison — local alignment File I/O Chapter 14 Homework 2 Wed Oct 14 Significance of similarity scores Conditionals (Krzywinski and Altman, 2013), Chapter 5 Mon Oct 19 Multiple testing correction For loops (sample.txt, seq-pvalues.txt) Chapter 7 Homework 3 Wed Oct 21 Motif search More for loops (sequences.txt, matrix.txt) Mon Oct 26 Motif p-values More for loops (my-pssm.txt))   Homework 4 Wed Oct 28 FDR control (pvalues.txt) While loops (Noble 2009) Mon Nov 2 Motif discovery Dictionaries (small-scores.txt, mapping.txt, quants.txt) (D'haeseleer 2006) Homework 5 The remainder of the lecture schedule will be posted soon. Mon Dec 14 Final exam, 8:30 am - 10:20 am