Statistics 166/366
Statistical Models in Biology
Spring 2010 ● Mon, Wed 11:00AM - 12:15PM ● McCullough 122
Professor Nancy Zhang
Announcements
Final project presentations
will be Friday, June 4, 3-6 pm. Click here for the schedule of presentations. The location is Sequoia Hall 200.
Contacts
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Office / Office hours |
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Instructors |
Nancy
Zhang (nzhang) |
Sequoia 141, 1:30-2:30 PM Mondays |
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TA |
Hao Chen (haochen) |
Sequoia
231, 4-5 PM Wednesdays |
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Pre-requisite
Basic probability and
statistics at the level of Stats 116 and Stat 200.
Tentative Syallabus (Links will work after the lecture)
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Week |
Date |
Topic |
Reading |
Slides /
code |
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1 |
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1 |
29-Mar |
Introduction,
course logistics |
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2 |
31-Mar |
EM |
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3 |
5-Apr |
Estimating
isoform expression. Guest lecturer:
Hui Jiang, Stanford Univ. |
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4 |
7-Apr |
Hidden Markov
Models |
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3 |
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6 |
14-Apr |
HMM example
I: DNA copy number estimation |
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5 |
12-Apr |
HMM example II:
fastPHASE |
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4 |
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7 |
19-Apr |
Monte Carlo integration,
rejection method |
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8 |
21-Apr |
Rejection method
example: coalescent |
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5 |
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9 |
26-Apr |
Metropolis-Hastings
algorithm |
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10 |
28-Apr |
Gibbs sampling |
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6 |
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11 |
3-May |
Metropolis-Hastings
example |
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12 |
5-May |
Gibbs sampling
example |
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7 |
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13 |
10-May |
Network models
in biology Guest lecturer: Jie Peng, UC Davis |
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14 |
12-May |
Network models
in biology. Guest lecturer: Haiyan
Huang, UC Berkeley |
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8 |
13 |
17-May |
Bootstrap |
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14 |
19-May |
Bootstrap
example: phylogenetic analysis |
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9 |
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15 |
24-May |
Scan statistics
for genome-wide profiling. |
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16 |
26-May |
Multi-sample scan
statistics and data integration. |
Slides |
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10 |
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19 |
31-May |
Project
presentations |
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20 |
02-June |
Project
presentations |
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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
Course requirements
There will be
three assignments, and one final projects.
All will require some programming with R.
Homework
1. (Due April 26) Solutions
Homework
2. (Due May 10)
Homework
3. (Due May 26) X.txt,
XY.txt
Final
Project Guidelines (Due June 4, 3 pm)
Grading
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Homeworks: |
60% |
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Final Project: |
40% |