You have decided to build. What comes next?
The first conversation settles direction and scope. Once the project is worth pursuing, we work with you to organize the data relationships, define the core usage paths, run a platform trial and make clear how updates and maintenance will be handled after launch.
A project usually goes through four stages
A smaller project can take a lighter path, while a complex one spends more time on data design and the trial run. How far each step goes is set by the scope both sides confirm.
- 01Direction and boundary assessment
First assess whether the existing data is worth turning into a resource and which form fits better: internal use, shared collaboration, public release, a paper-linked resource or an upgrade of an existing platform. This clarifies the research question, the intended users, data ownership and what is left out of scope for now.
Deliverable a direction assessment and a scope note - 02Data and resource design
Organize samples, projects, analysis results, paper figures and supplementary tables around the confirmed research tasks, and design the fields, data relationships, evidence sources, versioning rules and access boundaries.
Deliverable a data asset inventory, fields and resource structure - 03Platform development and trial run
Develop search, browsing, visualization, download and permission features for the confirmed use cases, then run a trial with core samples, genes, figures and typical usage paths.
Deliverable a trial-ready version and acceptance records - 04Launch, handover and maintenance
Confirm the launch scope, citation and download notes, permissions and responsible owners, and produce a version that can be handed over. Later updates, intake of new projects and operational support are provided only within the agreed project handover scope.
Deliverable a live resource, handover documentation and maintenance boundaries
At each stage, who prepares what
The scientific content needs the research group's confirmation, while data curation, platform development and testing are carried out by GeneSight within the agreed scope. At the end of each stage, both sides can see a concrete result.
| Stage | What your team prepares | What GeneSight handles | Deliverable |
|---|---|---|---|
| Direction and boundary assessment | Research direction, existing data types, primary users, openness goals and current platform problems | Sort out the research tasks, team capacity and the support that needs to be added, then assess the resource form, the development boundary and whether the next step is worth taking | a direction assessment and a scope note |
| Data and resource design | Sample and project lists, data file locations, the paper and supplementary materials, terminology and permission requirements | Complete the data inventory, identifiers and field design, and build traceable links between data and evidence | a data asset inventory, fields and resource structure |
| Platform development and trial run | Confirm the core content, typical usage paths and acceptance rules, and review the scientific content and display boundaries promptly | Complete data ingestion, page and feature development, testing and fixes, making sure every entry point maps to a clear data source | a trial-ready version and acceptance records |
| Launch, handover and maintenance | Confirm the launch content, open license, update cadence and who is responsible afterward | Complete the launch and handover, the version notes and maintenance support within the agreed scope; new data, features or deployment needs are confirmed separately | a live resource, handover documentation and maintenance boundaries |
- What your team prepares
- Research direction, existing data types, primary users, openness goals and current platform problems
- What GeneSight handles
- Sort out the research tasks, team capacity and the support that needs to be added, then assess the resource form, the development boundary and whether the next step is worth taking
- Deliverable
- a direction assessment and a scope note
- What your team prepares
- Sample and project lists, data file locations, the paper and supplementary materials, terminology and permission requirements
- What GeneSight handles
- Complete the data inventory, identifiers and field design, and build traceable links between data and evidence
- Deliverable
- a data asset inventory, fields and resource structure
- What your team prepares
- Confirm the core content, typical usage paths and acceptance rules, and review the scientific content and display boundaries promptly
- What GeneSight handles
- Complete data ingestion, page and feature development, testing and fixes, making sure every entry point maps to a clear data source
- Deliverable
- a trial-ready version and acceptance records
- What your team prepares
- Confirm the launch content, open license, update cadence and who is responsible afterward
- What GeneSight handles
- Complete the launch and handover, the version notes and maintenance support within the agreed scope; new data, features or deployment needs are confirmed separately
- Deliverable
- a live resource, handover documentation and maintenance boundaries
The three problems most likely to slow a project down
Sample names, groups, batches and processing information are inconsistent, making the data hard to search and reuse later.
Expression matrices, differential analysis, enrichment results and figure sources cannot be mapped to one another, which makes it harder to recheck the paper or hand the work to a new member.
Data updates, field changes and figure exports go unrecorded, which tends to cause confusion during long-term maintenance.
Frequently asked questions
Not sure how the project should start?
The first conversation does not need a complete plan. Describe the research subject, the data you already have and the current difficulty, and we will first assess whether the project is worth pursuing and which step is the better place to start.