Query Workflows¶
Atlas query workflows are designed around explicit dataset identity and explicit selectors. The query layer prefers clarity over permissive ambiguity.
Query Shape¶
flowchart LR
Request[Request] --> Dataset[release species assembly]
Dataset --> Selector[gene_id region name filters]
Selector --> Policy[limits and policy checks]
Policy --> Response[structured response]
This query shape makes the request contract explicit. Atlas wants dataset identity, selectors, and policy checks to be visible rather than hidden inside vague endpoint behavior.
Most Useful Query Endpoints¶
/v1/datasets/v1/version/v1/genes/v1/genes/count/v1/genes/{gene_id}/transcripts/v1/transcripts/{tx_id}/v1/query/validate
Use Explicit Selectors¶
flowchart TD
Broad[Broad unbounded query] --> Reject[policy rejection]
Explicit[Explicit selector such as gene_id or region] --> Execute[query executes]
This selector diagram is here to set expectations early. Atlas is designed to reject some expensive or ambiguous scans instead of silently turning them into unsafe runtime work.
The server will reject some broad scans unless they are explicitly allowed. For a reliable first query, prefer selectors such as:
gene_idregion- bounded limits
Good First Queries¶
curl -s "http://127.0.0.1:8080/v1/version"
curl -s "http://127.0.0.1:8080/v1/datasets"
curl -s "http://127.0.0.1:8080/v1/genes?release=110&species=homo_sapiens&assembly=GRCh38&gene_id=g1&limit=1"
curl -s "http://127.0.0.1:8080/v1/genes/count?release=110&species=homo_sapiens&assembly=GRCh38&gene_id=g1"
Validate a query shape before execution:
curl -s \
-H 'Content-Type: application/json' \
-d '{"release":"110","species":"homo_sapiens","assembly":"GRCh38","gene_id":"g1","limit":"1"}' \
http://127.0.0.1:8080/v1/query/validate
Query Workflow Advice¶
- always include release, species, and assembly
- prefer explicit selectors over wide scans
- use
query/validatewhen teaching clients how to form requests - treat policy rejection as signal, not as a nuisance to work around blindly
What a Healthy Query Workflow Looks Like¶
- the request names the dataset identity explicitly
- the selector is narrow enough to satisfy policy
- the client can explain whether a failure is validation, policy, or missing data
Purpose¶
This page explains the Atlas material for query workflows and points readers to the canonical checked-in workflow or boundary for this topic.
Stability¶
This page is part of the canonical Atlas docs spine. Keep it aligned with the current repository behavior and adjacent contract pages.