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The Wisconsin Chapter of the American Statistical Association
proudly presents
The 2015 Annual Meeting: Big Data and Statistics
sponsored by
The ASA Section on Statistical Graphics
and Revolution Analytics
When: June 5
Where: Marquette University
Raynor Library Conference Center
https://www.google.com/maps/place/1355+W+Wisconsin+Ave,+Milwaukee,+WI+53233 Parking: Wells Street Parking Structure
https://www.google.com/maps/place/1240+W+Wells+St,+Milwaukee,+WI+53233 12:45-01:00 Registration
01:00-01:15 Welcome and Introduction
01:15-02:15 First Keynote
02:15-03:15 Second Keynote
03:15-03:30 Break
03:30-04:30 Third Keynote
04:30-05:00 Networking
05:30-? Dinner with the Speakers
Current members of WI Chapter or Section on Statistical Graphics; and students: $20
New/former members: $29
You can make reservations via PayPal <
elsmith@mcw.edu> or
send a check made out to The Wisconsin Chapter of the ASA
The Medical College of Wisconsin
Center for Patient Care & Outcomes Research
PO Box 26509
Milwaukee, WI 53226
ATTN: Elizabeth Smith
Keynote Speakers
Yuan Ji
Director of Biomedical Informatics
NorthShore University HealthSystem
Associate Professor, University of Chicago
http://health.bsd.uchicago.edu/yji/index.html Title: Zodiac -- A comprehensive depiction of genetic interactions in
cancer by integrating TCGA data
Abstract: The Cancer Genomes Atlas (TCGA) data are unique in that
multimodal measurements across genomics features, such as copy number,
DNA methylation, and gene expression, are obtained on matched tumor
samples. The multimodality provides an unprecedented opportunity to
investigate the interplay of these features. Graphical models are
powerful tools for this task that address the interaction of any two
features in the presence of others, while traditional correlation- or
regression-based models cannot. We introduce Zodiac, an online
resource consisting of two main components, 1) a large database
containing nearly 200 million interaction networks of multiple
genomics features produced by applying novel Bayesian graphical models
on TCGA data through massively parallel computation, and 2) analytics
tools that perform high-quality inference on data-enhanced
networks. Setting a new way of integrating TCGA data, Zodiac, publicly
available at <http://www.compgenome.org/ZODIAC>, is expected to
facilitate the generation of new knowledge and hypotheses by the
community.
David Smith
Chief Community Officer
Revolution Analytics
https://www.linkedin.com/in/dmsmith Title: Reproducible Data Science with R
Abstract: Good data science is reproducible. If someone else can't
independently replicate your results from your data, the consequences
can be severe. Using an open-source data science language like R is a
good first step for reproducibility, and I'll introduce a new system
for R that manages a changing ecosystem of versions and packages to
ensure reliable results.
Ming Yuan
Professor, Department of Statistics
Senior Investigator, Morgridge Institute for Research
University of Wisconsin-Madison
http://www.stat.wisc.edu/~myuan Title: Journey into the "world of data"
Abstract: We live in an information era. Immediate access to copious
amounts of data provides unprecedented opportunities but also creates
new challenges, particularly on how to turn them into actionable
insights. Through several examples from my recent academic research, I
will share with you a few lessons learned in dealing with these new
challenges.
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Rodney Sparapani
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