55
Sun, 8/8/2021,
3:30 PM -
5:20 PM
Virtual
Statistical methods for data from single cell technologies — Contributed Speed
Section on Statistics in Genomics and Genetics
Chair(s): Pixu Shi, Duke University
3:35 PM
Reconstructing Single-Cell Trajectories via Stochastic Tree Search
Jingyi Zhai, University of Michigan ; Hui Jiang, University of Michigan
3:40 PM
RZiMM-ScRNA: A Regularized Zero-Inflated Mixture Model Framework for Single-Cell RNA-Seq Data
William Bekerman, Department of Statistics and Data Science, Cornell University
3:45 PM
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
3:50 PM
Estimating Heterogeneous Gene Regulatory Networks from Zero-Inflated Single-Cell Expression Data
3:55 PM
A Fast and Efficient Likelihood Approach for Genome-Wide Mediation Analysis Under Extreme Phenotype Sequencing
4:00 PM
Deconvolution of Spatial Transcriptomics Data Using Penalized Bayesian Non-Negative Matrix Factorization
4:05 PM
Overview of Simultaneous Inference of Relative Gene Isoform Expressions for RNA Sequencing Factorial Designs
4:10 PM
Extension of the Condition-Adaptive Fused Graphical Lasso and Application to Modeling Brain Region Co-Expression Networks
4:15 PM
SCRIP: An Accurate Simulator for Single-Cell RNA Sequencing Data
4:20 PM
ZIRFs: Zero-Inflated Random Forests for Estimating Gene Regulatory Networks from Single Cell RNA-Seq Data
4:30 PM
Hierarchical Canonical Correlation Screen for Identification and Visualization of Phenotype-Driven Cell Types in Multiple Sample Single-Cell RNA-Sequencing Experiments
4:35 PM
On the Semiparametric Efficiency of a Class of Functional Response Models for Between-Subject Attributes
4:40 PM
SpotClean Adjusts for Spot Swapping in Spatial Transcriptomics Data
4:45 PM
Comparative Analysis of Statistical Methods for Single-Cell RNA Sequencing Data
4:50 PM
Single-Cell Unbiased Visualization with SCUBI
4:55 PM
Lamian: A Statistical Framework for Differential Pseudotime Analysis in Multiple Single-Cell RNA-Seq Samples
5:00 PM
Flexible Copula Model for Integrating Correlated Multi-Omics Data from Single-Cell Experiments
5:05 PM
A New Algorithm to Decipher Patterned Heterogenous Networks
5:10 PM
Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition
