Space life sciences have been revolutionized by the paradigm shift of biology into a “big data” era. Spaceflight experiments are now routinely generating large-scale molecular (“omics”) datasets across different tissues and organisms to help better understand the mechanisms of health decline in space. Large-scale study of gene expression (“transcriptomics”) has proven to be a particularly useful for producing new insights into the signaling pathways and key molecules that underpin maladaptation to spaceflight. Technologically, bulk RNA-sequencing provides a simple yet powerful platform for studying transcriptome-wide dysregulation in space. This chapter outlines a basic pipeline for analyzing bulk RNA-sequencing data using R, a well-established programming tool for transcriptomics. The pipeline is demonstrated throughout via application to RNA-sequencing data from a real-life spaceflight experiment, and is provided as a single-resource code script (available at: https://github.com/williscrg/MiMB-Space-RNAseq-Pipeline ) that the reader can use to run the pipeline from start to finish “as is” or with modification if/as desired or required.