Next-Generation Sequencing Methods The goal of this project is to develop statistical methods for the analysis of next-generation sequencing data sets. Participants Vishal Sarsani Shai He Publications Model-based identification of conditionally-essential genes from transposon-insertion sequencing data, bioRxiv (2021) A Bayesian Nonparametric Model for Inferring Subclonal Populations from Structured DNA Sequencing Data, Annals of Applied Statistics (2021) SCSIM: Jointly simulating correlated single-cell and bulk next-generation DNA sequencing data, BMC Bioinformatics (2020) Next project: MAP Clustering →