ArticleMethods in molecular biology (Clifton, N.J.)2026
Transcriptomics in Space: A Basic R Pipeline for Analyzing Bulk RNA-Sequencing Data.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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