1. Tree-guided regression and multivariate analysis of microbiome data - Hongu Zhao and Tao Wang.- 2. Computational methods for metagenomic assemblies and strain identification - Hongzhe Li.- 3. Graphical models for microbiome data - Ali Shojaie.- 4. Bayesian models for understanding the modulating factors of microbiome data - Francesco Denti, Matthew D. Koslovsky, Michele Guindani, Marina Vannucci, and Katrine L. Whiteson.- 5. Use of variable importance in microbiome studies - Hemant Ishwaran.- 6. Log-linear models for microbiome data - Glen Satten.- 7. Quantification of amplicon sequences in microbiome samples using statistical methods - Karin Dorman.- 8. TBD - Jeanine Houwing Duistermaat.- 9. Analyzing microbiome data by employing the power of abundance ratios - Zhigang Li.- 10. Beta diversity analysis - Michael Wu.- 11. MicroPro: using metagenomic unmapped reads to provide insights into human microbiota and disease associations - Fengzhu Sun.- 12. Statistical methods for feature selection in microbiome studies - Peng Liu.- 13. A Bayesian restoration of the duality between principal components of a distance matrix and operational taxonomic units in microbiome analyses - Somnath Datta and Subharup Guha.