Shai He Defends Thesis

Shai He successfully defended his thesis titled, “Statistical Methods to Study Transposon Sequencing Data: Nonparametric Bayesian Models with Sampling Algorithms”. Thanks to Profs. Anna Liu, Leili Shahriyari, and Peter Chien for serving on his committee. Congratulations Dr. He!

Paper: Model-based identification of conditionally-essential genes from transposon-insertion sequencing data

Our paper on transposon sequencing has been published in PLOS Computational Biology. The full article is available at here.

Summary: Transposon insertion sequencing allows the study of bacterial gene function by combining next-generation sequencing techniques with transposon mutagenesis under different genetic and environmental perturbations. Our proposed regularized negative binomial regression method improves the quality of analysis of this data.