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VIDEOS: 3rd Workshop on Statistical and Algorithmic Challenges in Microbiome Data Analysis – Day 2

Tuesday, April 2

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Senthil Kumar Muthiah: A Scale Normalization Strategy For The Correction Of Compositional Bias In Sparse Sequencing Count Data
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Pratheepa Jeganathan: Bayesian Inference For Removing Contamination In Microbiome Studies
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Benjamin Callahan: Consistent And Correctable Bias In Metagenomic Sequencing Measurements
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Greg Gloor : A Probabilistic Compositional Effect Size Metric For Use In Microbiome Datasets
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David Clausen : Detecting and Correcting for Differential Detection Effects in 16S Data
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Alex Washburne: Phylofactorization - Identifying Lineages Of Interest In Microbiome Datasets
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Javier Rivera-Pinto: Selbal: An R Package For The Identification Of Microbial Signatures
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Lu Huang: Balance Regression In Microbiome Studies Using Stochastic Search
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M. Luz Calle: Weighted Kernel Machine Regression For Microbiome Compositional Data Analysis
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Susan P. Holmes: Challenges In The Analyses Of Multidomain Longitudinal Data: Layered Solutions.
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Christian Diener: Near-Causal Inference With Time-Ordered Association Testing For Multiomic Time Series
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Antonie Bodein: A Generic Multivariate Framework For The Integration Of Microbiome Longitudinal Studies With Other Data Types
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Joshua Harrison: A Bayesian, Probabilistic Method For Analyzing Multinomially Distributed Data.
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Jiyuan Hu: Joint Modeling Of Longitudinal Microbiome And Time-To-Event Data With Application To A Type I Diabetes Study
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Justin Silverman: Scalable Bayesian Multinomial Logistic-Normal Models For The Analysis Of Microbiome Data
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Travis Gibson: Robust And Scalable Models Of Microbiome Dynamics
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Cameron Martino: Elucidating Microbial Spatiotemporal Dynamics With Compositional Tensor Factorization
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Evan Bolyen: QIIME 2 Enables Robust And Reproducible Bioinformatics
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