July 2026

From Building to Growing, Together

Jianguo (Jeff) Xia, PhD

For the better part of a decade, the work had a single shape: build. We built a tool for each kind of omics data, one at a time, then set about bringing them onto a single platform – and alongside them a book to explain not just how each analysis runs, but why. This summer, both are ready. The 2026 edition of Omics Data Science is complete, and the OmicsVerse platform now carries the tools, the workflows, and the reasoning behind them together in one place.

Building was the first half of the work. Learning together – and growing what we have built with the people who use it – is the half that matters most.

The Book Is Ready

The 2026 edition is the most complete version yet: 476 pages and 114 figures across twelve chapters, moving from the shared foundations of omics data through transcriptomics, proteomics, metabolomics, and the microbiome, into multi-omics integration and the changing role of AI. It is written to be the map – the reasoning behind each analysis, when it applies, and how to read what it returns. Every workflow on the platform follows the framework laid out in its pages.

476
Pages
114
Figures
12
Chapters

The Tools Are Ready

The platform side is ready too. The Workflow Library now holds more than 130 grounded workflows – 100 single-tool analyses and 32 advanced, multi-step pipelines – each built from the same peer-reviewed tools researchers have relied on for years: MetaboAnalyst, MicrobiomeAnalyst, ExpressAnalyst, ProteoAnalyst, miRNet, OmicsNet, and OmicsAnalyst. Nothing in it is a black box. You bring your data; the workflows carry it from raw values to a report whose every step you can trace – on our cloud, or your own machine.

A book you can stand behind, and workflows you can audit. That is the foundation – deliberately built to be dependable rather than magical, so that everything we do next can stand on it.

The Path Forward: Learn and Grow Together

Having the book and the tools is the groundwork, not the finish line. A method only helps if you know when to trust it, and that kind of judgment is built together – by working through real analyses, asking hard questions, and learning from one another. So the next chapter of this work is not more software. It is community.

Two things anchor it, and both are meant to bring people in rather than sell a course:

1
A webinar series, mapped to the book. Chapter by chapter, each session takes one topic, works a real dataset through the matching workflow, and leaves room for your questions. Open to the community and built to be followed alongside the text.
2
Live, guided training for going deeper. The multi-omics bootcamp (August 17–21) for an intensive week, and the weekly Fall course (Saturday mornings, September–November), each session tied to a chapter of Omics Data Science.

None of this is about the software for its own sake. It is about making sure the people who use these tools can verify and guide their own analysis with confidence – the whole reason we set out to build self-service analysis in the first place.

Grow Together

A book and a platform are a starting point, not an endpoint. What they become depends on the questions you bring to them – the edge cases, the new data types, the workflows that do not quite exist yet. We would rather build the next stretch of the road with you than for you.

So join a webinar, sit in on a session, or simply tell us what you are stuck on. The tools and the book are ready; the best of this work is still ahead, and it is easier to reach together.

Learn with us

Read the book, explore the training and webinar series built around it, and grow with the community.

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