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SAGES Program — June 7, 2019

9:00-9:45	Registration and light breakfast. Click here for the program and abstract booklet.
9:45-10:00	Welcome and opening remarks: Marcella Devoto (CHOP and University of Pennsylvania)
Session 1	Moderator: Ingo Ruczinski (Johns Hopkins University)
10:00-10:30	Rasika Mathias (Johns Hopkins University): Pushing the boundaries of whole genome sequencing: from genotype to phenotype with a few extras in between
10:30-11:00	Blanca Himes (University of Pennsylvania): Enhancing Electronic Health Record-derived data with data from secondary sources to address multifactorial problems in real life populations
11:00-11:30	Nicola Camp (Huntsman Cancer Institute): Reframing tumor heterogeneity: gene mapping and precision treatments
11:30-1:00	Lunch
12:00-1:00	Poster Session 1 (odd numbered posters)
Session 2	Moderator: Joan Bailey-Wilson (NHGRI)
1:00-1:15	Anupama Jha (University of Pennsylvania): Interpretation of deep learning models in genomics: splicing codes as a case study
1:15-1:30	Gao Wang (University of Chicago): Statistical methods for multi-condition genetic finemapping with applications to eQTL discovery in human tissues
1:30-2:00	Braxton Mitchell (University of Maryland): The genetic architecture of LDL cholesterol in the Amish
2:00-2:30	Peter Kraft (Harvard University): Using polygenic risk scores for breast cancer to inform screening: model fit, calibration, and utility
2:30-3:30	Coffee break and Poster Session 2 (even numbered posters)
Session 3	Moderator: Barbara Engelhardt (Princeton University)
3:30-3:45	Poster Awards Presentation
3:45-4:15	Justin Silverman (Duke University): Scalable Bayesian multinomial logistic-normal models for the analysis of sequence count data
4:15-4:45	Katie Pollard (Gladstone Institutes & UCSF): Genetic variation and regulation of the 3D genome
4:45-6:00	Conclusion and Cocktail reception

SAGES Program — June 1, 2018

9:00-9:45	Registration and light breakfast
9:45-10:00	Welcome and opening remarks: Marcella Devoto (CHOP and University of Pennsylvania)
Session 1	Moderator: Barbara Engelhardt (Princeton University)
10:00-10:30	Hilary Finucane (Broad Institute and Harvard): Identifying disease-relevant cell types from GWAS data
10:30-11:00	Michael Hoffman (University of Toronto): Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome
11:00-11:30	Wei Sun (Fred Hutchinson Cancer Research Center): Omic data-based biomarkers for cancer immunotherapy
11:30-1:00	Lunch
12:00-1:00	Poster Session 1 (odd numbered posters)
Session 2	Moderator: Maja Bucan (University of Pennsylvania)
1:00-1:15	Kelsey Johnson (University of Pennsylvania): Identifying recurrent mutations from unphased population-level sequencing data
1:15-1:30	Yasmmyn Salinas (Yale University): A comparison of univariate and multivariate GWAS methods for analysis of multiple dichotomous phenotypes
1:30-2:00	Shyamal Peddada (University of Pittsburgh): Constrained statistical inference for the analysis of microbiome data
2:00-2:30	Iain Mathieson (University of Pennsylvania): Tracking complex traits over space and time with ancient DNA
2:30-3:30	Coffee break and Poster Session 2 (even numbered posters)
Session 3	Moderator: Iuliana Ionita-Laza (Columbia University)
3:30-4:00	Stephanie Santorico (University of Colorado Denver): Genetic risk prediction for complex traits and its relationship to sub-phenotypes in vitiligo
4:00-4:30	Jeffrey Leek (Johns Hopkins): Improving the value of public genomic data with phenotype prediction
4:30-5:30	Conclusion and Cocktail reception

SAGES Program — June 9, 2017

9:00-9:45	Registration and light breakfast
9:45-10:00	Welcome and opening remarks, Harold I. Feldman (University of Pennsylvania)
Session 1	Moderator: Hongzhe Li (University of Pennsylvania)
10:00-10:30	Tuuli Lappalainen (New York Genome Center): Quantifying genetic regulatory variation affecting each gene in human populations
10:30-11:00	Christina Kendziorski (University of Wisconsin): Statistical methods for single-cell RNA-seq experiments
11:00-11:30	Rafael Irizarry (Harvard University): Overcoming Bias and Batch Effects in single cell and bulk RNAseq Data
11:30-1:30	Lunch and Two Poster Sessions
Session 2	Moderator: Joan Bailey-Wilson (National Human Genome Research Institute)
1:30-2:00	Haky Im (University of Chicago): Genome, phenome, and what happens in between
2:00-2:30	William C. L. Stewart (Nationwide Children’s): Leveraging 1000 Genomes to Improve Disease Gene Localization
2:30-3:00	Tim Thornton (University of Washington): Challenges and New Approaches for Complex Trait Mapping in Ancestrally Diverse Populations
3:00-3:30	Coffee break
Session 3	Moderator: Ingo Ruczinski (Johns Hopkins University)
3:30-4:00	Elizabeth Grice (University of Pennsylvania): Metagenomic and genomic analysis of host-microbe interactions of the skin
4:00-4:30	Barbara Engelhardt (Princeton University): Intersecting pathology images and gene expression data to understand drivers of complex phenotypes
4:30-5:30	Conclusion and Cocktail reception

From Phenotype to Genotype and Everything In-Between: New Computational Tools for Disease Gene Discovery — June 3, 2016

Advances in technology and significant decrease in the associated costs are driving progress in genomic studies. Studies of whole exome and genome sequences of complex traits in large samples are becoming increasingly common. Other sources of high-dimensional information, including expression, epigenetic, metabolic and microbiomic data, are also being collected in disease and control samples. To fully understand the complex bases of human disease and trait variation, all of these factors should be properly considered in a unified analytical framework, together with epidemiological data on environmental exposures and other risk factors. SAGES brings together an interdisciplinary group of scientists working in the fields of genomics, epidemiology, and statistics, to address these challenges. The forum provides an opportunity for scientists at all levels in their career to convene and review new developments in these areas of research. The symposium aims to facilitate exchange of ideas and promote interactions and collaborations among participants.

Program

9:30-10:15	Registration and light breakfast
10:20-10:30	Welcome and opening remarks
Session 1	Moderator: Nandita Mitra (University of Pennsylvania)
10:30-11:00	Itsik Pe’er (Columbia University): Replicability and winner's curse in genome-wide association studies
11:00-11:30	Andrew Allen (Duke University): Robust analysis of secondary phenotypes in case-control genetic association studies
11:30-12:00	Christoph Lange (Harvard University): Substructure in whole-genome sequencing studies: detection and adjustment procedures
12:00-1:30	Lunch and Poster Session
Session 2	Moderator: Peter Kanetsky (Moffitt Cancer Center)
1:30-2:00	Kimberly Siegmund (University of Southern California): Reconstructing the starts of human tumors
2:00-2:30	Jill Barnholtz-Sloan (Case Western University): Advances in brain tumor research: Leveraging BIG data for BIG discoveries
2:30-3:00	Chris Amos (Dartmouth College): Understanding etiology of lung and common cancers
3:00-3:30	Coffee break
Session 3	Moderator: Blanca Himes (University of Pennsylvania)
3:30-4:00	Christopher Brown (University of Pennsylvania): Genetics of gene expression: from rare to common, from ubiquitous to cell specific
4:00-4:30	Alexis Battle (Johns Hopkins University): Understanding the impact of rare regulatory variation
4:30-5:30	Conclusion and Cocktail reception

Beyond DNA Sequencing: Emerging Challenges in Quantitative Genomic Analysis — May 29, 2015

Program

10:00-10:20	Registration and light breakfast
10:20-10:30	Harold Feldman (CCEB, University of Pennsylvania): Welcome and opening remarks
Session 1	(Moderator: Ingo Ruczinski, Johns Hopkins University)
10:30-11:00	Richard Bonneau (New York University): Connecting the Immune System and the Microbiome through Dynamic Network Inference
11:00-11:30	Mingyao Li (University of Pennsylvania): Statistical Modeling of RNA Sequencing Data
11:30-12:00	Jianxin Shi (National Cancer Institute): Detection of Regulatory Hotspots in Highly Dimensional Genomic Data
12:00-1:30	Lunch and Poster Session
Session 2	(Moderator: Iuliana Ionita-Laza, Columbia University)
1:30-2:00	Hongkai Ji (Johns Hopkins University): Big Data Methods for Dissecting Variations in High-Throughput Genomic Data
2:00-2:30	Stephen Montgomery (Stanford University): Identifying the Extent and Impact of Rare Non-Coding Variants
2:30-3:00	Eleazar Eskin (University of California Los Angeles): Known and Unknown Confounding Factors in Genetic Studies
3:00-3:30	Coffee break
Session 3	(Moderator: Joan Bailey-Wilson, National Human Genome Research Institute)
3:30-4:00	Xihong Lin (Harvard University): Analysis of Integrated Genetics and Genomics
4:00-4:30	Nancy Cox (Vanderbilt University): Getting to Real Integration Across Omics
4:30-5:00	Final discussion and conclusions

Integrated Systems Biology Analytical Methods for Epidemiological Studies of Complex Traits — May 30, 2014

Advances in genomic technology and significant decrease in the associated costs are driving progress in genetic studies for disease gene identification. Studies of whole exome and genome sequences of complex traits in large samples will become increasingly common. Other sources of high-dimensional information, including expression, epigenetic, metabolic and microbiomic data, are also being commonly collected in disease and control samples. To fully understand the complex bases of human disease, all of these factors should be properly considered in a unified analytical framework, together with epidemiological data on environmental exposures and other risk factors. To discuss how to address the analytical challenges presented by these sources of data, the Center for Genetics and Complex Traits of the Perelman School of Medicine at the University of Pennsylvania organized the 2014 Mid-Atlantic Genetic Epidemiology and Statistics (MAGES) conference: Integrated systems biology analytical methods for epidemiological studies of complex traits.

Program

10:00-10:20	Arrival and light breakfast
10:20-10:30	Harold Feldman (CCEB Director, University of Pennsylvania): Welcome and opening remarks
Session 1: Analysis of complex datasets
10:30-11:00	Dana Crawford (Vanderbilt University): Leveraging epidemiologic and clinical collections for genomic studies of complex traits
11:00-11:30	Dan Nicolae (University of Chicago): Methodological challenges in the transition from GWAS to sequencing
11:30-12:00	John Storey (Princeton University): Genetic and epigenomic determinants of environment-specific gene expression differences
12:00-1:30	Lunch
Session 2: Statistical models for integrated analytical methods
1:30-2:00	Sandrine Dudoit (University of California, Berkeley): Normalization and Differential Expression in RNA-Seq
2:00-2:30	Jun Zhu (Mount Sinai Medical School): Dynamic causal models for studying complex traits
2:30-3:00	Joel Bader (Johns Hopkins University): Gene-based and pathway-based tests of association
3:00-3:30	Coffee break
Session 3: Future developments in high-dimensional data analysis
3:30-4:00	Hongzhe Li (University of Pennsylvania): Integrative approaches to genomic studies of complex diseases
4:00-4:30	Marylyn Ritchie (Pennsylvania State University): Data fusion in the omic universe
4:30-5:30	Roundtable and Conclusions (Moderator: Andreas Scherer, Golden Helix)

Methods and Applications in the Next Generation Sequencing Age — May 17, 2013

The Center for Genetics and Complex Traits (CGACT) of the University of Pennsylvania hosted a one-day conference on Genetic Epidemiology and Statistics: Methods and Applications in the NGS Age, on May 17, 2013 at the Sheraton Philadelphia University City Hotel near the campus of the University of Pennsylvania in Philadelphia, PA.

The conference intended to bring together an interdisciplinary group of scientists working in the fields of statistical genetics and genetic epidemiology. The forum provided an opportunity for faculty, postdoctoral fellows, and graduate students working in these fields to convene and review new developments in these areas of research. The program featured three sessions with three invited speakers each and allowed for formal as well as informal discussion. The conference aimed to facilitate exchange of ideas and promote interactions and collaborations among participants.

The 2013 MAGES Conference was sponsored by the Center for Clinical Epidemiology and Biostatistics (CCEB) of the University of Pennsylvania.

Program

10:15-10:30	Timothy Rebbeck & Harold Feldman (Penn): Welcome and opening remarks
Session 1: GWAS developments and applications (Moderator: Danish Saleheen, Penn)
10:30-11:00	Tara Matise (Rutgers): The Next PAGE: Examples from the Population Architecture using Genomics and Epidemiology Study
11:00-11:30	Hongyu Zhao (Yale): Incorporating prior information in GWAS: how far can we go?
11:30-12:00	Nilanjan Chatterjee (NCI): Risk prediction based on hidden heritability in genome-wide association studies
12:00-1:30	Lunch
Session 2: New methods in statistical genetics (Moderator: Jinbo Chen, Penn)
1:30-2:00	Ingo Ruczinski (Johns Hopkins): Methods for genetic studies with case-parent trios
2:00-2:30	Jaya Satagopan (MSKCC): Evaluation of statistical interactions for binary traits
2:30-3:00	Kathryn Roeder (Carnegie Mellon): Estimating genetically inferred relationships using Treelets
3:00-3:30	Coffee Break
Session 3: Analysis of NGS data (Moderator: Mingyao Li, Penn)
3:30-4:00	Iuliana Ionita-Laza (Columbia): Sequence-based association tests and applications
4:00-4:30	Joan Bailey-Wilson (NHGRI): Family-based strategies for analyses of next generation sequence data
4:30-5:00	Adam Naj (Penn): Filter Feeding: Principled exploratory filtering approaches for sequence data to identify variants, genes, and regions for genetic follow-up studies
5:00-5:30	Hongzhe Li (Penn): Conclusions

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