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.