A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data

A 4-state HMM provides an improved way of analyzing Tn-seq data and assessing different levels of essentiality that enables not only the characterization of essential and non-essential genes, but also genes whose disruption leads to impairment (or enhancement) of growth.