JSM2025
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Contributed Posters

Contributed Poster Presentations: Section on Statistics in Genomics and Genetics

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-Hall B Music City Center
Shirin GolchiChair
Section on Statistics in Genomics and Genetics

18 Presentations

41: Addressing Heterogeneous Sensitivity in Biomarker Screening with Application in NanoString nCounter
2:00 PM - 3:50 PM
Co-authors: Chang Yu, Zhijin Wu (Brown University), Chang Yu
High-throughput biomarker screeningBinary biomarkerDetection sensitivitySample-and-feature-specific sensitivityHypothesis testingNanoString nCounter
42: Application of the STAAR Framework in Detecting Rare Variant Associations with Alzheimer's Disease and Related Dementias: Insights and Implications
2:00 PM - 3:50 PM
Co-authors: Dongyu Wang (Department of Biostatistics, Boston University School of Public Health), Dongyu Wang (Department of Biostatistics, Boston University School of Public Health), Nancy Heard-Costa (Department of Medicine, Boston University School of Medicine;NHLBI Framingham Heart Study), Andy Rampersaud (Research Computing Services, Information Services & Technology, Boston University), Eden Martin (University of Miami-Miami Institute of Human Genomics), Adam Naj (Department of Biostatistics, Epidemiology, and Informatics, Department of Pathology and Laboratory), Bilcag Akgun (John P Hussman Institute for Human Genomics), Brian Kunkle (John P Hussman Institute for Human Genomics; John T Macdonald Department of Human Genetics), Gina Peloso, Anita DeStefano (Department of Biostatistics, Boston University School of Public Health), Xihao Li (University of North Carolina at Chapel Hill), Seung Hoan Choi (Department of Biostatistics, Boston University School of Public Health)
Rare varaint analysisSTAAR frameworkAlzheimer's disease
43: Comparison of Linear Mixed-Effect and Deep Learning Models for Predicting Phenotypes using GWAS
2:00 PM - 3:50 PM
Co-authors: Muhammad Danish, Muhammad Danish, Yingying Wei (The Chinese University of Hong Kong)
Genome-Wide Association Studies (GWAS)Linear Mixed-Effect ModelsDeep LearningBiobank
44: Detecting and quantifying mediation of health outcomes by microbial communities
2:00 PM - 3:50 PM
Co-authors: Haoyue Li, Emma Accorsi (Harvard T. H. Chan School of Public Health), Haoyue Li, Eric Franzosa (Harvard T. H. Chan School of Public Health), Nicole Levesque (Harvard T. H. Chan School of Public Health), Siyuan Ma (Vanderbilt University Medical Center), Curtis Huttenhower (Harvard School of Public Health)
human microbiomemediation analysismicrobiome epidemiologymetagenomics
45: Drug-DMsim: A Novel Pipeline for Inferring Drug MOA via Differential Module Similarity
2:00 PM - 3:50 PM
Co-authors: Jiaqi Li (National Institute of Environmental Health Sciences), Jiaqi Li (National Institute of Environmental Health Sciences), Komlan Atitey (National Institute of Environmental Health Science (NIEHS)), Benedict Anchang (NIEHS)
Drug discoverymechanism of action (MOA)gene regulatory network (GRN)Differential modularityDimensionality reductionLINCS
46: Extending Sparse CCA for Multi-Population, Multi-Feature Integration
2:00 PM - 3:50 PM
Co-authors: Renee Ge, Quefeng Li (University of North Carolina Chapel Hill), Renee Ge, Yuchao Jiang (Texas A&M University)
Sparse Canonical Correlation AnalysisData IntegrationVariance DecompositionSingle-Cell Multiomics
48: Inference of Heterogeneous Effects in Single-cell Genetic Perturbation Screens
2:00 PM - 3:50 PM
Co-authors: Zichu Fu, Zichu Fu, Lin Hou (Tsinghua University)
single-cell RNA-seqgenetic perturbationcausal inferenceheterogeneous effectsdeep learning
49: Interpretable Ordinal Analysis for Complex Designs in Cell and Molecular Biology
2:00 PM - 3:50 PM
Co-authors: Carson Stacy (University of Arkansas), Carson Stacy (University of Arkansas), Jeffrey Lewis (University of Arkansas)
Ordinal dataOrdinal RegressionCumulative Link ModelsInteraction TermsProportional OddsOrdinal Superiority Measure
50: Joint FDR Control Under Multiple Conditions
2:00 PM - 3:50 PM
Co-authors: Sara Tyo, Sara Tyo, Zhaoxia Yu (University of California, Irvine)
statistical powerfalse discovery rategene expression analysishigh-dimension
51: Likelihood-based inference of migration surfaces
2:00 PM - 3:50 PM
Co-authors: Jiatong Liang, Jiatong Liang, Jonathan Terhorst (University of Michigan)
migration surfacedemographic inferencepopulation genetics
52: M6A Peak Calling Accounting for Sequencing Bias Across Regions and Samples
2:00 PM - 3:50 PM
Co-authors: Lanyu Zhang, Lanyu Zhang, ZHENXING GUO, Zhaohui Qin (Emory University), Zhijin Wu (Brown University)
transcriptionRNA methylationm6AMeRIP-seq
53: Nonparametric Denoising of Microbiome Metagenomics Data
2:00 PM - 3:50 PM
Co-authors: Mukai Wang, Mukai Wang, Gen Li (University of Michigan)
Microbiome metagenomicsDenoiseBinarizationMatrix factorizationNonparametric
54: Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments
2:00 PM - 3:50 PM
Co-authors: Haoran Lu (University of Georgia), Haoran Lu (University of Georgia), Luyang Fang (University of Georgia), Wenxuan Zhong (University of Georgia), Guo-Cheng Yuan (Dana-Farber Cancer Institute), Ping Ma (University of Georgia)
Spatial TranscriptomicsGene Panel SelectionSelf-supervised learningDeep learningRegularization
55: Raman Spectra using wavelet-based ANOVA: Uncovering Dietary-Gene Spectral Components in Mice
2:00 PM - 3:50 PM
Co-authors: Jaeseon Lee (Texas A&M University), Jaeseon Lee (Texas A&M University), Brani Vidakovic (Texas A&M University, Statistics Department), Patrick Stover (Texas A&M University), Regan Bailey (Texas A&M University), Alicia Carriquiry (Iowa State University)
Raman SpectroscopyWavelet TransformWANOVAFANOVA
57: SpaDiff: Denoising for Sequence-based Spatial Transcriptomics via Diffusion Process
2:00 PM - 3:50 PM
Co-authors: Jiazhang Cai, Jiazhang Cai, Yongkai Chen, Luyang Fang (University of Georgia), Guocheng Yuan (Icahn School of Medicine at Mount Sinai), Wenxuan Zhong (University of Georgia), Ping Ma (University of Georgia)
Sequence-based Spatial TranscriptomicsData DenoisingDiffusion ProcessScore FunctionLangevin MCMC
58: Sparse Bayesian Partially Identified Models Enhance Differential Abundance and Expression Analyses
2:00 PM - 3:50 PM
Co-authors: Won Gu, Won Gu, Justin Silverman (Penn State University)
Compositional DataBayesian Partially Identified ModelSparsity AssumptionType-I and Type-II ErrorsUncertainty Quantification
59: Stage-Specific BIN1 Effects Link Tau to Preclinical Functional Connectivity in Alzheimer's Disease
2:00 PM - 3:50 PM
Co-authors: Yan Yan (Vanderbilt University), Yan Yan (Vanderbilt University), Rui Chen (Vanderbilt University), Ke Xu (Vanderbilt University Medical Center), Xue Zhong (Vanderbilt University Medical Center), Yuting Tan (Vanderbilt University), Anshul Tiwari (Vanderbilt University), Zhexing Wen (Emory University), Bingshan Li (Vanderbilt University), Hakmook Kang (Vanderbilt University)
multi-group SEMmediation analysisAlzheimer’s diseasefunctional connectivityBIN1tau pathology
60: TPClust: Temporal Profile-Guided Disease Subtyping Using High-Dimensional Omics Data
2:00 PM - 3:50 PM
Co-authors: Boyi Hu (Columbia University), Badri Vardarajan (Columbia University), Boyi Hu (Columbia University), Philip De Jager (Columbia University), David Bennett (Rush Alzheimer Disease Center), Yuanjia Wang (Columbia University), Annie Lee (Columbia University Irving Medical Center)
Disease subtypingMachine learningSemi-parametric modelHigh-dimensional omicsLongitudinal dataSupervised clustering
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