2014-15: Bioinformatics: Statistical and Computational Challenges in Omics Data Integration (SCC-ODI): February 16-17, 2015


This workshop was held at SAMSI in Research Triangle Park, NC.


The focus of the workshop was to examine the statistical and computational challenges arising from the analysis and interpretation of diverse types of omics data (genomics, proteomics, genetics, etc). The workshop featured current and ongoing research work by two working groups within the Beyond Bioinformatics program. The Cancer Genome Atlas (TCGA) group is exploring the inference of cancer subtypes, and multidimensional outcome predictions through the joint analysis of diverse data types. The Chronic Obstructive Pulmonary Disease (COPD) working group is exploring the biological problems that include studying multivariate disease phenotypes, using omic data for sub-type identi cation, in depth exploration of GWAS results and identifying pathways associated with disease. Statistical tools explored in the working groups include graphical models, kernel machines, unsupervised learning, survival prediction, and pathway and network analysis. One of the main purposes of this mid-program workshop is for the two working groups to meet and discuss common approaches, present updates and interact face-to-face. The target audience was the regular working group participants which include a mix of students, post-doctoral fellows and junior and senior faculty.

Participants optionally submitted an abstract for a short presentation at a Poster session held on Monday (Feb 16th, 2015) evening. A small subset of the submitted abstracts were selected for short presentations at the workshop.

Questions: email bioinformatics@samsi.info

Schedule and Supporting Media

Participant List
Speakers Titles/Abstracts

Monday, February 16, 2015

Time Description Speaker Slides Videos
8:00-8:30 Registration
8:30-8:45 Introduction and Welcome Sujit Ghosh, SAMSI
Katerina Kechris, University of Colorado Denver
Session 1 Chair: Ronglai Shen, Memorial Sloan Kettering Cancer Center
8:45-9:30 Sparse Regression Incorporating Graphical Structure Among Predictors Yufeng Liu, University of North Carolina
9:30-10:00 A Bayesian Model for the Identification of Differentially Expressed Genes in Daphnia Magna Exposed to Munition Pollutants Alberto Cassese, Rice University pdf
10:00-10:30 Break
Session 2 Chair: Hongyu Zhao, Yale University
10:30-11:00 Identifying Disease Heterogeneity from Gene Expression Data by Integrating Pathway Information Xiting Yan , Yale University
11:00-11:30 A Bayesian Approach to Biomarker Selection through miRNA Regulatory Networks Francesco Stingo, MD Anderson Cancer Center
11:30-12:00 Sparse Analysis of High Dimensional Data with Application to Data Integration Sandra Safo, Emory University pdf
12:00-12:30 Network-Based Pathway Enrichment Analysis of Omics Data Ali Shojaie, University of Washington
12:30-1:30 Lunch
Session 3: Working Group Updates Chair: Katerina Kechris, University of Colorado Denver
1:30-2:00 Integrating Clinical and Molecular Data for Survival Prediction in TCGA Bin Zhu, NCI
2:00-2:30 Exploratory Study of Gene Expression in COPD Using Network Analysis and Kernel Machine Methods Junxiao Hu, University of Colorado – Denver
2:30-3:00 Discovery of Novel Loci Associated with COPD by Pulling Information from Case-control status, Related Clinical Feature, and Functional Annotation Jiehuan Sun, Yale University pdf
3:00-3:30 Post-GWAS Prioritization Through Integrated Analysis of Functional Annotation Qiongshi Lu, Yale University pdf
3:30-4:00 Break
Session 4: Keynote Talk Chair: Veera Baladandayuthapani, MD Anderson Cancer Center
4:00-5:00 Keynote Speaker
Integrating Data, Assays, and Pathways: The 20,000 Foot View
Keith Baggerly, MD Anderson Cancer Center
5:00-7:00 Poster Session and Reception

Tuesday, February 17, 2015

Time Description Speaker Slides Videos
8:30-8:45 Registration and Announcements Katerina Kechris, University of Colorado Denver
8:45-10:30 TCGA and COPD Working Group Breakout Sessions
SAMSI Room 150
NISS Room 104
10:30 Adjourn