Studying bacterial transcriptomes using RNA-seq

TL;DR: Artemis is presented as a tool for integrated visualization and computational analysis of different types of HTS datasets in the context of a reference genome and its corresponding annotation.

TL;DR: The feasibility of taking transcriptomics one step further by performing 'dual RNA-seq', in which gene expression changes in both the pathogen and the host are analysed simultaneously, is assessed.

TL;DR: The results suggest that Rockhopper can be used for efficient and accurate analysis of bacterial RNA-seq data, and that it can aid with elucidation of bacterial transcriptomes.

TL;DR: Focusing on sequence-based discovery of antibiotic resistance genes, this Review discusses computational strategies and resources for resistance gene identification in genomic and metagenomic samples, including recent deep-learning approaches.

TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.

TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.

TL;DR: Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors.