Statistical Challenges and Breakthroughs in Diabetes and Obesity Research in the Big Data Era — Topic-Contributed Papers
Section on Bayesian Statistical Science, Section on Statistics in Genomics and Genetics, Section on Statistics in Epidemiology
Organizer(s): Xiang Liu, University of South Florida
Chair(s): Kristian F. Lynch, University of South Florida
3:35 PM
Longitudinal Plasma Metabolome and Circulating Vitamins Stratified Onset Age of an Initial Islet Autoantibody and Progression to Type 1 Diabetes: The TEDDY Study Qian Li, St. Jude Children’s Research Hospital; Xiang Liu, University of South Florida; Jimin Yang, University of South Florida; Iris Erlund, Finnish Institute for Health and Welfare; Åke Lernmark, Lund University; William Hagopian, Pacific Northwest Research Institute; Marian Rewers, University of Colorado Denver; Jin-Xiong She, Augusta University; Jorma Toppari, University of Turku; Anette-G Ziegler, Technical University of Munich; Beena Akolkar, NIDDK/NIH; Jeffrey Krischer, University of South Florida
MLG: Multilayer Graph Clustering for Multi-Condition ScRNA-Seq Shan Lu, University of Wisconsin-Madison; Daniel Conn, University of Wisconsin-Madison; Shuyang Chen, University of Wisconsin-Madison; Kirby Johnson , University of Wisconsin-Madison; Emery Bresnick, University of Wisconsin-Madison; Sunduz Keles, University of Wisconsin, Madison
SpotClean Adjusts for Spot Swapping in Spatial Transcriptomics Data
Presentation
Zijian Ni, UW-Madison; Aman Prasad, Department of Dermatology, UW-Madison; Shuyang Chen, University of Wisconsin-Madison; Lisa Arkin, Department of Dermatology, UW-Madison; Richard Halberg, Department of Medicine, UW-Madison; Beth Drolet, Department of Dermatology, UW-Madison; Michael Newton, University of Wisconsin, Madison; Christina Kendziorski, UW-Madison
Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition Yang Guo, University of Victoria; Fatemeh Esfahani, University of Victoria; Xiaojian Shao, National Research Council Canada; Venkatesh Srinivasan, University of Victoria; Alex Thomo, University of Victoria; Li Xing, University of Saskatchewan; Xuekui Zhang, University of Victoria
In the Pipeline: Statistical Advances to Preserve Biological Signal in High-Throughput, Single-Cell Imaging and Sequencing Methods — Topic-Contributed Papers
Section on Statistics in Imaging, Section on Statistics in Genomics and Genetics, ENAR
Organizer(s): Coleman R Harris, Vanderbilt University Medical Center
Comparison of Normalization Methods to Combine Batches of High-Dimensional Multiplexed Images
Presentation
Coleman R Harris, Vanderbilt University Medical Center; Qi Liu, Vanderbilt University Medical Center; Eliot McKinley, Vanderbilt University Medical Center; Joseph Roland, Vanderbilt University Medical Center; Ken Lau, Vanderbilt University Medical Center; Robert Coffey, Vanderbilt University Medical Center; Simon N Vandekar, Vanderbilt University
Statistical Methods for Multi-Omic Data Analysis — Topic-Contributed Papers
Section on Statistics in Genomics and Genetics, Biometrics Section, Section on Statistics in Epidemiology, Caucus for Women in Statistics
Organizer(s): Wei Sun, Fred Hutchinson Cancer Research Center
Chair(s): Chad (Qianchuan) He, Public Health Sciences Division, Fred Hutch
1:35 PM
Individual-Level Differential Expression Analysis for Single Cell RNA-Seq Data Si Liu, Fred Hutchinson Cancer Research Center; Mengqi Zhang, University of Pennsylvania; Zhen Miao, University of Washington; Fang Han, University of Washington; Raphael Gottardo, Fred Hutchinson Cancer Research Center; Wei Sun, Fred Hutchinson Cancer Research Center
1:55 PM
Bayesian Inference on Multilayered Non-Normal Graphical Models Min Jin Ha, University of Texas MD Anderson Cancer Center; Moumita Chakraborty, University of Texas MD Anderson Cancer Center; Anindya Bhadra, Purdue University; Veerabhadran Baladandayuthapani, University of Michigan
2:15 PM
Cell Type-Specific Expression Quantitative Trait Loci Paul Little, Fred Hutchinson Cancer Research Center; Yun Li, UNC-Chapel Hill; Danyu Lin, University of North Carolina at Chapel Hill; Wei Sun, Fred Hutchinson Cancer Research Center
Statistical methods for genomic and epigenetic data analysis — Contributed Speed
Section on Statistics in Genomics and Genetics
Chair(s): Daniel Conn, University of Wisconsin-Madison
1:35 PM
A Method for Subtype Analysis with Somatic Mutations Meiling Liu, Fred Hutchinson Cancer Research Center; Yang Liu, Wright State University; Michael C Wu, Fred Hutchinson Cancer Research Center; Li Hsu, Fred Hutchinson Cancer Research Center; Qianchuan He, Fred Hutchinson Cancer Research Center
Association Test Using Copy Number Profile Curves (CONCUR) Enhances Power in Rare Copy Number Variant Analysis Amanda Brucker, Duke University; Jung-Ying Tzeng, North Carolina State University; Wenbin Lu, North Carolina State University; Rachel Marceau West, North Carolina State University; Qi-You Yu, National Taiwan University; Chuhsing Kate Hsiao, National Taiwan University; Tzu-Hung Hsiao, Taichung Veterans General Hospital; Ching-Heng Lin, Taichung Veterans General Hospital; Patrik K. E. Magnusson, Karolinska Institutet; Patrick F Sullivan, University of North Carolina at Chapel Hill; Jin P. Szatkiewicz, University of North Carolina at Chapel Hill; Tzu-Pin Lu, National Taiwan University
Genetic Correlation Between Major Depression and Objectively Assessed Sleep Features in a Community Cohort from Lausanne, Switzerland Wei Guo, National Institutes of Health; Sun J Kang, National Institutes of Health; Giorgio Pistis, Lausanne University Hospital and University of Lausanne ; Lihong Cui, NIMH; Andrew Leroux, University of Colorado Anschutz Medical Campus; Vadim Zipunnikov, Johns Hopkins Bloomberg School of Public Health; Martin Preisig, University Hospital of Lausanne; Kathleen Merikangas, National Institute of Mental Health
A Two-Part Linear Mixed Model with Shared Random Effects for Longitudinal Microbiome Compositional Data Yongli Han, National Cancer Institute/National Institutes of Health; Danping Liu, National Cancer Institute/National Institutes of Health; Jianxin Shi, National Cancer Institute/National Institutes of Health; Emily Vogtmann, National Cancer Institute/National Institutes of Health; Courtney Baker, University of North Carolina at Chapel Hill; Xing Hua, Fred Hutchison Cancer Research Center
MeningiOMICS: A Web-Based Meningioma 'Omics' Data Analysis and Visualization Tool Using R Shiny Kaitlyn Lucrezia O'Shea, Northwestern University, Feinberg School of Medicine, Department of Preventive Medicine; Anh Tran, Northwestern University, Feinberg School of Medicine, Department of Neurological Surgery; Craig Horbinski, Northwestern University, Feinberg School of Medicine, Department of Pathology; Denise Scholtens, Northwestern University, Feinberg School of Medicine, Department of Preventive Medicine
Statistical Analysis of Longitudinal Microbiome Data Amy Pan, Medical College of Wisconsin; Vy Lam, PITA Analytics; Samantha N. Atkinson, Medical College of Wisconsin; Nita Salzman, Medical College of Wisconsin; L Silvia Munoz-Price, Medical College of Wisconsin
Tumor Cell Total MRNA Expression Shapes the Molecular and Clinical Phenotype of Cancer Shaolong Cao, University of Texas MD Anderson Cancer Center; Jennifer Rui Wang, University of Texas MD Anderson Cancer Center; Shuangxi Ji, University of Texas MD Anderson Cancer Center; Peng Yang, University of Texas MD Anderson Cancer Center; Jonas Demeulemeester, KU Leuven; Peter Van Loo, The Francis Crick Institute; Wenyi Wang, University of Texas MD Anderson Cancer Center
RAREsim: A Simulation Method for Very Rare Genetic Variants Megan Null, The College of Idaho; Josée Dupuis, Boston University; Christopher R Gignoux, University of Colorado Anschutz Medical Campus; Audrey E Hendricks, University of Colorado Denver
A Multi-Tissue, Multi-Trait Model for Omics Data Samantha Lent, Boston University; Ching-Ti Liu, Boston University; Marie-France Hivert, Harvard Medical School; Josée Dupuis, Boston University
Summix: A Method for Detecting and Adjusting for Population Structure in Genetic Summary Data Ian S. Arriaga-MacKenzie, University of Colorado Denver; Gregory Matesi, University of Colorado Denver; Samuel Chen, University of Colorado Denver; Alexandria Ronco, University of Colorado Denver; Katie M. Marker, University of Colorado Anschutz Medical Campus; Jordan R. Hall, University of Colorado Denver; Ryan Scherenberg, University of Colorado Denver; Mobin Khajeh-Sharafabadi, University of Colorado Denver; Yinfei Wu, University of Colorado Denver; Christopher R Gignoux, University of Colorado Anschutz Medical Campus; Megan Null, The College of Idaho; Audrey E Hendricks, University of Colorado Denver
Novel Statistical Methods for Microbiome Data Analysis — Topic-Contributed Papers
Section on Statistics in Genomics and Genetics, Biometrics Section, ENAR
Organizer(s): Xiang Zhan , Penn State University
Chair(s): Arun Srinivasan, Penn State University
4:05 PM
Controlled Microbiome Variable Selection Analysis Xiang Zhan , Penn State University; Arun Srinivasan, Penn State University; Lingzhou Xue, Penn State University and National Institute of Statistical Sciences