Rice: STAT 670 Statistical Genetics GSBS: GS110033 (Methods in Genetic Epidemiology-Linkage) Instructors

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Rice:

STAT 670 Statistical Genetics


GSBS: GS110033 (Methods in Genetic Epidemiology
-
Linkage)


Instructors
:

MDA:

Chris Amos (
camos@mdanderson.org
)

Sanjay Shete (
sshete@
mdanderson.org
)

Bo Peng (bpeng@mdanderson.org)

Ivan Gorlov

(
ipgorlov@mdanderson.org)

Paul Scheet (
permutations@gmail.com)


Dakai Zhu (
dkz
@mdanderson.org
),
Data Coordinator/Systems Manager


Rice:

Rudy Guerra (
rguerra@rice.edu
), 713.348.5453

Tel: 713
-
792
-
3020

Fax: 713
-
792
-
8261



Accounts
:

Student0
-
Student10 (password: student) @ penrose.md
acc.tmc.edu or
request.mdacc.tmc.edu


Purpose
:


The purpose of this course is to provide students with training in methods of
statistical
genetics, especially
genetic epidemiology designed to identify genetic factors. This course
provides instruction on
tools of genetic linkage for both simple and complex diseases. We will also
instruct students in the use of some association methods for gene discovery and may describe some
data mining tools. The course teaches both the theory and application of some co
mmonly used
methods for linkage and association analysis. In this course we will focus on discrete traits or
diseases.


Target Audience:


The target audience includes students with backgrounds or interests in population genetics, genetic
epidemiol
ogy, sta
tistics, epidemiology,
molecular biology. Theoretical discussions require
knowledge of probability, some

statistics and some calculus. Although the course will largely be
self
-
contained a basic course in mathematical statistics will prove very useful.
We
will also use
computer applications which will require the student to apply programs running in a unix
environment.


Location

and Time
:

Cancer Prevention Building 7.3555 (except
March 16
, an alternative space will be used).

Time:
8:30
-
10
,
Tuesday
,
Thursday
.


Grades:


Grades are assigned according to completion of homework
and data
projects. There will

not be any
examinations
.

We anticipate that students will provide written responses to homework including a
summary of their findings. Each homework assignm
ent will be due within 2 weeks after it has been
assigned unless other
wise noted, and we will deduct 10

points from the maximal grade for each
additional week that elapses.



Textbook
s
:

The
recommended

textbook
s

for the class
are

A Statistical Approach t
o Genetic
Epidemiology: Concep
ts and Applications
,
by Andreas Ziegler, Inke R. Koenig
. Wiley (2006).
ISBN 3527312528


Statistical Genetics:

Gene Mapping through Linkage and Association.

Neale
BM,

Ferreira
MAR,

Medland
SE,
& Posthuma D (Eds.) Taylor and Fr
ancis, London (2007). ISBN 9780415410403


DATE

TOPIC

Lecturer

Location

M, Jan 11

Introduction to problems of statistical genetics Basic Genetics I:
Mendel, Genes, Genotypes

Amos

CPB
7.3555

W, Jan 13

Basic Statistics: Testing (
t
, χ
2
, ANOVA
, likelihood
)

Gu
erra

RM1 (8) CPB

T, Jan 19

Likelihood


formulation and introduction of Estimation

Amos

CPB7.3555

Th
, Jan 2
1

Optimization methods

Shete

CPB7.3555

T, Jan 26

Population Genetics I: HWE, Allele estimation

Shete

CPB7.3555

TH, Jan 28

Population Genetics II
: Departures from HWE

Amos

CPB7.3555

T, Feb 2

Population Genetics III: Allele estimation, using Linkage

Shete

CPB7.3555

TH, Feb 4

ITO Matrices and correlations in relatives

Amos

CPB7.3555

T, Feb 9

Population Genetics effect on HWE and LD

Peng

CPB7.3555

TH, Feb 11

Identity in State and Identity by Descent

Shete

CPB7.3555

T, Feb 16

Resemblance & Correlation between Relatives

Genetic Variance Components

Shete

CPB7.3555

TH, Feb 18

Using IBD information for model
-
free tests

Amos

CPB7.3555

T, Feb 23

Ha
seman
-
Elston and Variance Components Tests

Amos

CPB7.3555

TH, Feb 25

Pedigree Analysis


Elston
-
Stewart Algorithm

Amos

CPB7.3555

T, Mar 2

Linkage Analysis


Fastlink Software (ext peds)

Amos

CPB7.3555

TH, Mar 4

Linkage Analysis


Lander
-
Green Algorith
m (LGA)

Amos

CPB7.3555

Mar 8
-
12

Spring Break


CPB7.3555

T, Mar 16

Markov Chain Monte Carlo (MCMC)


Theoretical aspects

Amos

CPB7.3555

TH, Mar 18

Markov Chain Monte Carlo


fitting using LOKI

Ma

CPB7.3555

T, Mar 23

Joint Segregation and Linkage

Wu

CPB7
.3555

TH, Mar 25

Association studies using LD

Guerra

CPB7.3555

T, Mar 30

Tagging SNPs and design of association studies

Guerra

CPB7.3555

TH, Apr 1

Population Structure
-
effects and corrections

Amos

CPB7.3555

T, Apr 6

Family Association Tests I

Haplotyp
e Relative Risk, TDT

Shete

CPB7.3555

TH, Apr 8

Family Association Tests II

TDT and Pedigree Tests

Shete

CPB7.3555

T, Apr 13

Simulation Approaches

Peng

CPB7.3555

TH, Apr 15

MetaAnalysis for Association and Linkage

Guerra

CPB7.3555

T, Apr 20

Sequencin
g and Genetic Studies

Scheet

CPB7.3555

TH, Apr 22

The 1000 Genomes Project

Scheet

CPB7.3555

T, Apr 27

Imputation

Scheet

CPB7.3555

TH, Apr 29

Gene
-
Environment Interactions

Shete

CPB7.3555

T, May 4

Gene
-
Gene Interaction Analysis

Shete

CPB7.3555

TH, May 6

Machine Learning Tools for Genetic Epidemiology

Shete

CPB7.3555


Bayesian Networks and Intermediate Phenotypes

Shete

CPB7.3555