Genomics Studio (2026-US-PO-2888)

The rapid growth of high-throughput omics technologies has created a need for integrated, user-friendly tools that enable robust and scalable analysis of complex biological data. In JMP Pro, we introduce Genomics Studio, a new add-in that organizes end-to-end omics analysis around six biological domains — Genetics, RNA-seq, Microbiome, Single Cell, Proteomics, and Multi-Omics — each opening into its own guided workflow built around the methods and terminology researchers in that domain already use.

Rather than a rigid, linear pipeline, each workflow presents a suggested sequence of import, preprocessing, and analysis steps that a user can run in any order, in full or in part, depending on their data and question. A global keyword search surfaces the matching tool or platform directly by name, letting experienced users bypass menu navigation entirely. Genomics Studio is built primarily on JMP's native statistical engine; where JMP does not yet offer a given analysis, the platform calls out to Python as additional support, and can optionally connect to R and Bioconductor for further coverage — all without requiring the user to switch tools or environments.

Across the six domains, the platform currently supports quality control, missing-data imputation, and normalization (including CLR normalization for compositional microbiome data); exploratory and multivariate analyses such as PCA, PCoA, UMAP, and Leiden clustering; and inferential and modeling methods including GWAS, predictive modeling, differential expression and abundance testing, enrichment analysis, PERMANOVA, variance components, marker gene identification, and multi-omics joint integration via CCA. Every method links directly to its documentation and citation, and completed analyses can be exported as a self-contained HTML review that requires no add-in or JMP license to view.

Genomics Studio is under active development, with domain coverage expanding over time; because any step can call a Python script or an R connection, new methods can be added without architectural changes. By combining statistical rigor with a guided, searchable interface, Genomics Studio lowers the barrier to advanced omics analysis while preserving analytical depth — providing a unified environment that reduces workflow fragmentation and accelerates discovery in the life sciences.