Genetics 245 / Statistics 345
Computational
Algorithms for Statistical Genetics
Spring 2009 ● TuTh 11:00AM - 12:15PM ● Alway
Building Room M104
Professors
Hua Tang and Nancy Zhang
Announcements
05/30/09: Nick will hold extra office hours on Monday, June 1, 2:30-3:30 pm.
05/28/09: Hua will move her office hours next week to Wed, 12-1 pm instead of Thurs 3:30-4:30.
05/05/09: You need to submit a half page proposal of your final project on May 14, along with your homework 2.
05/01/09: Homework 2 is posted [here]
04/16/09: Homework 1 is posted [here]
04/13/09: For this week only, Nick will hold office hour on Friday instead of Wednesday.
The first class meeting, 3/31, will be held in Alway
M114.
Contacts
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Office
/ Office hours |
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Instructors
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Hua
Tang (huatang) |
Alway
M335,
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Nancy
Zhang (nzhang) |
Sequoia 141,
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TA |
Nick
Johnson (nickaj) |
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Course email |
gen245@gmail.com |
Please use this address for course-related
emails |
Tentative Syallabus
Slides for the lectures will
be available here, or at the mirroring site [here].
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Week |
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Date |
Topic |
Lecturer |
Reading |
Slides /
code |
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1 |
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1 |
31-Mar |
Introduction,
course logistics |
HT |
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2 |
2-Apr |
Likelihood &
Bayesian inference |
NZ |
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3 |
7-Apr |
EM |
HT |
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4 |
9-Apr |
HMM |
HT |
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3 |
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5 |
14-Apr |
HMM example I:
fastPHASE |
HT |
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6 |
16-Apr |
Monte Carlo
integration, rejection method |
HT |
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4 |
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7 |
21-Apr |
HMM example II:
conserved element |
NZ |
Siepel et al. Genome Research, 2005. Siepel et al. supplementary materials. |
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8 |
23-Apr |
Rejection method
example: coalescent |
HT |
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5 |
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9 |
28-Apr |
Metropolis-Hastings
algorithm |
HT |
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10 |
30-Apr |
Gibbs sampling |
NZ |
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6 |
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11 |
5-May |
Gibbs sampling
example |
NZ |
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12 |
7-May |
Metropolis-Hastings
example |
HT |
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7 |
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13 |
12-May |
Bootstrap |
NZ |
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14 |
14-May |
Bootstrap
example: phylogenetic analysis |
HT |
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8 |
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15 |
19-May |
Bootstrapping correlated
data. Example: genomic profiling |
NZ |
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16 |
21-May |
Multiple
hypothesis testing |
NZ |
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9 |
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17 |
26-May |
Scan statistics
& change point models |
NZ |
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18 |
28-May |
Scan statistics
example |
NZ |
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Course requirements
There will be three
assignments, and one final projects. All will require some programming.
Homework 1. (Due April 30) Homework 1 Solutions
Homework 2. (Due May 14) Homework 2 Solutions
Homework 3. (Due June 2) For problem 3: X.txt, XY.txt
Final Project Guidelines (Due June 4)
Grading
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Homeworks: |
60% |
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Final Project: |
40% |
Pre-requisite
Basic probability at the level of Stats 116.
Textbook
There are no required texts for this class.
Reading materials to complement the lectures will be posted here or distributed
in class. Below is a partial list of books that covers some of the topics at a
more advanced level.
Statistical Analysis with Missing Data by Little & Rubin
Computational Statistics by Givens & Hoeting
An Introduction to the Bootstrap by Efron & Tibshirani
Monte Carlo Strategies in Scientific Computing by Jun Liu
Sequential Analysis by
David Siegmund
