Sage Bionetworks Training

brewerobstructionAI and Robotics

Nov 7, 2013 (3 years and 11 months ago)

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Sage Bionetworks Training


1





Sage Bionetworks Training



August 6
-
10 2012





Overview

This training will cover the following topics

Synapse

Learn about and how to use the Sage Bionetworks Synapse
system:

All data
used for the

training course is

hosted on Amazon EC2 instances

and accessed
via Synapse. All analysis will

be done in R using R
-
studio


Data Curation and Normalization

Learn how to QC, curate, and normalize data in Synapse


Genetic Analysi
s

Learn the principles behind GWA Studies. Understand how the associations
between gene expression and genetics can help interpret disease associations.



Pathway Analysis

Learn how to use pathway analysis methods such as SNP Set Enrichment
Analysis (SSEA)

and Gene Set Variation Analysis (GSVA)



Network analysis

Learn the principles and biological sources of gene co
-
expression and
differential co
-
expression. Understand how to incorporate genetic information
and other priors to find directed relationships b
etween genes in Bayesian
networks. Learn how to identify Key Drivers in networks, and how to make
inferences about causality



Predictive Modeling


Learn how to use machine learning and other algorithms

for high dimensional
predictive modeling


Data
Visualization

Visualize data in R and Cytoscape







Sage Contacts

Mette

Peters
mette.peters@sagebase.org

206
-
617
-
1163


Chris Gaiteri
chris.gaiteri@sagebase.org


717
-
891
-
7541


Address

Sage Bionetworks

1100
Fairview Ave. N.

Seattle, WA 98109

Instructors

Adam Margolin (
margolin@sagebase.org
)

Brig Mecham
(brig.mecham@sagebase.org)

Chris Gaiteri (
chris.gaiteri@sagebase.org)

Dave Burdick
(
david.burdick@sagebase.org
)

Elias Neto (
neto@sagebase.org
)

Erich
Huang

(
erich.huang@sagebase.org
)

Jonathan D
erry (
derry@sagebase.org
)

Justin Guinney

(
justin.guinney@sagebase.org
)

In Sock Jang

(
in.sock.jang@sagebase.org
)

Matt Furia (
matt.furia@sagebase.org
)

Solly Sieberts
(
solly.sieberts@sagebase.org
)

Tools

Synapse

-

RStudio

-

Cytoscape


Other Resources

Training materials for each Day/Session

R Client Setup

Sage Bionetworks Website

Sage / DREAM breast cancer prognosis
challenge

Short Introduction to Synapse Video




Sage Bionetworks Training


1


Day
1

-

Location: M1
-
A30
5

Session I



Setup

9am


12pm

Instructors: Matt

Furia
/Dave Burd
ick




Introduction to Synapse



R
-
studio and cloud computing



R
-
Synapse


Session II

-

Data Normalization

1pm
-
5pm

Instructors: Matt Furia
/Brig M
echam




Synapse curation pipeline



SVA, SNM
-

tutorial and metaGEO curation





Day 2
-

Location: M1
-
C103

Session I

-

Principles of co
-
expression

9
am
-
12pm

Instructor: Chris Gaiteri




Biological sources of co
-
expression

o

A discussion of the many ways that coordinated expression arises



Statistical options for inferring networks

o

Alternatives to plain correlations, their pros/cons

1pm
-
3pm

Instructor: Chris Gaiteri




Graph theoretic network properties

o

What can we learn from the organization of these networks? Can their structure be their function?



Differential co
-
expression networks

o

More technical questions of how we can be sure that a disease
-
state network is significantly different than
a healthy state network


Session II



Data visualization in Cytoscape

3pm
-
4
pm

Instructor: Chris Gaiteri










Sage Bionetworks Training


2


Day 3
-

Location: M2
-
B102

Session I

-

BFRM, factor modeling

9
-
10
am

Instructor:
Erich Huang

Session I
I

-

Networks

10
am
-
12pm
/1pm
-
2pm

Instructor:
Elias Neto
/
In Sock Jang




Causal Inference



Bayesian networks



Aracne



Aracne and Bayesian network demo


Session I
II

-

High
-
dimensional factorization and predictive modeling

2pm
-
5pm

Instructors: Adam Margolin/Justin
Guinney



Science online demo



Predictive modeling in high dimensions

o

Topics cover
ed will include use of SVD, SVD
regression, and pe
nalized regression (e.g. ridge, lasso, and
ElasticNet)


Day 4
-

Location: M1
-
C103

Session I


Key Driver analysis

10am
-
11am

Instructor: Justin Guinney


Session II
-

Pathway Analysis

12:30pm
-
3:30
pm

Instructors:
Justin Guinney/Solly Siberts



GSEA & GSVA



GWAS,

eSNP & SNP Set Enrichment Analysis (SSEA)














Sage Bionetworks Training


2


Day 5
-

Location: M1
-
C103

Session I:

Experimental validation of network results

9:30
-
11am

Instructor: Jonathan Derry


Session II
: Application of methods learned du
ring the training using Roche

data

1pm


5pm

Instructor: Chris Gaiteri





























Sage Bionetworks Training


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