Genomica
SRUC developed software that helps researchers study microbes and their genes.
Making microbiome research easier
Microbiome research studies the communities of microbes, like bacteria and fungi, that live in environments such as the gut, soil and water, together with their genomes and the surrounding environmental conditions.
Created by Dr Salvatore Galgano at SRUC's Monogastric Science Research Centre, Genomica is a new software tool that helps scientists better understand large amounts of genetic data from microbes by transforming what is traditionally a long, complex, multi-step process into a fast, automated workflow -making research and analysis faster, easier to use, and less prone to human error.
Learn more about Dr Galgano and his work using the link below.
Where microbes meet meaning
Modern sequencing technologies can generate huge amounts of data showing which microbes and genes are present in a given environment, but interpreting what those changes actually mean can be difficult and time-consuming.
Genomica makes the entire process simpler by combining these complex steps into one: researchers simply input two files -one containing sequencing data and one containing sample information, and Genomica automatically carries out both statistical analysis and biological interpretation, and organises them into a single output folder that includes publication-ready figures and statistical and biological analysis.
To ensure robust and reliable results, Genomica software integrates established R-based analysis tools while applying statistical corrections. Importantly, it also carries out model diagnosis, allowing users to independently evaluate the adequacy of the analysis.
Genomica's streamlined workflow, alongside its ability to analyse around 4,000 orthologs in approximately three minutes, means scientists and researchers can focus more on the biology and less on the technical complexity of metagenomic analysis, making it easier to turn sequencing data into meaningful biological discoveries like how microbial communities respond to treatments, diets or environmental changes, and how these changes affect what microbes can do for their environments.
If you use Genomica, please cite using:
Galgano, S. Genomica: linear mixed model based, multiple hypothesis testing corrected, ortholog functional enrichment analysis. BMC Bioinformatics (2026). https://doi.org/10.1186/s12859-026-06450-y
Yu G, Chen M (2024). MicrobiomeProfiler: An R/shiny package for microbiome functional enrichment analysis. R package version 1.12.0, https://yulab-smu.top/contribution-knowledge-mining/, https://github.com/YuLab-SMU/MicrobiomeProfiler/.
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