Cells often respond in a distinct, dynamic and coordinated fashion to a specific pathogen, and this response is controlled by regulating the expression of genes. Transcriptomics is an approach that provides insight into this gene expression through the quantification and characterisation of ribonucleic acid (RNA) within a cellular sample. This can be done in a comprehensive or in a targeted manner depending on the application. Technological advances and reducing costs over the last 15 years have transformed the field of transcriptomics and as a result it has become an increasingly well-established research tool for infectious disease epidemiology. Comparing the abundance of RNA transcripts between samples from different disease states allows identification of differentially abundant transcripts, which enables the common and discriminatory features of the host response to a pathogen to be determined. This list of differentially abundant transcripts can be interrogated and profiled to infer function and provide biological insights into a disease or cellular process. Alternatively, it can be analysed to identify the minimal number of highly discriminating transcripts providing a disease signature, aiding biomarker and diagnostic discovery. In this chapter, we will introduce how transcriptomics is used in the field of infectious disease, discuss study design, common experimental and analytic approaches and their key limitations. Throughout the chapter, we will use the application of transcriptomics in tuberculosis as an exemplar.