Statistics Seminar - Pratheepa Jeganathan - Statistical Methods in Molecular Microbiology
- Mathematics & Statistics
- 10.27.2020 3:30 pm - 4:30 pm
Title: Statistical Methods in Molecular Microbiology
Speaker: Pratheepa Jeganathan (McMaster University)
Abstract: High-throughput sequencing generates massive molecular microbial datasets that pose several statistical challenges. There has been a substantial development in statistical methods to address contamination sequences from reagents, unequal sampling, unbounded and undetected taxa, sparsity, and heterogeneity. I will talk about the application of the Bayesian topic model to infer microbial communities [1,2] and differential topic analysis. I will use a previously analyzed plant microbiome dataset to demonstrate the statistical and R/Bioconductor/Stan tools available for this problem. In conclusion, I will discuss other opportunities that abound in applying Bayesian hierarchical methods to analyze molecular microbial data.
 D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, 3(Jan):993-1022, 2003.
 K. Sankaran and S. P. Holmes. Latent variable modeling for the microbiome. Biostatistics, 20(4):599-614, 2019.
Date/Time: Tuesday October 27, 3:30 - 4:30
Location: VirtualJoin Zoom Meeting
Meeting ID: 950 7922 1401