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Get Started Free →Build and operate reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. Use for DNAnexus data transfers, dxapp.json development, execution monitoring, workflow import, and project automation.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 74% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 36% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 80% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -13% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 36% | 0% |
Use this skill to build, run, and operate DNAnexus workloads without guessing at platform semantics. It covers:
dx CLI and dxpy automationdxapp.jsonThe documented baseline was verified on 2026-07-23 against dxpy==0.410.0, dxCompiler 2.17.0, and the 2026 DNAnexus documentation. Consult references/sources.md and current release notes when behavior may have changed.
DNAnexus operations can expose regulated data, delete immutable objects, change permissions, or incur compute and egress charges. Follow these rules:
and execution target before mutation.
material egress, archive/unarchive request, deletion, project removal, permission change, token revocation, or app publication unless the user already explicitly requested that exact operation and target.
deletion target from a non-unique name.
DX_SECURITY_CONTEXT or API tokens.Do not run dx env or dx env --bash in captured logs because both reveal the active token.
material to arbitrary hosts or user-controlled commands.
untrusted data. Quote shell arguments and pass subprocess arguments as arrays.
and organization policies. Do not copy data around a control.
output folders, cost limits, and bounded waits.
Install the CLI in an isolated tool environment:
bashuv tool install "dxpy==0.410.0" dx --version
For Python code in a project:
bashuv add "dxpy==0.410.0"
Use interactive login for human sessions:
bashdx login dx whoami dx select dx pwd
For non-interactive environments, inject only the named DNAnexus secret through the environment or a secret manager. Never echo it, include it in command output, commit it, or inspect the whole environment. See references/authentication.md.
Before acting, gather non-secret context:
bashdx --version dx whoami dx pwd dx ls
Then:
project-... IDs.open, closing, or closed) and archival state.dx run <executable> -h.and cost limit.
If shell environment variables conflict with the saved CLI session, follow references/authentication.md; do not expose either credential while diagnosing.
| Goal | Read first | Preferred interface | |---|---|---| | Build an app or applet | references/app-development.md | dx-app-wizard, dx build | | Configure dxapp.json | references/configuration.md | JSON plus validator script | | Transfer or organize data | references/data-operations.md | dx, Upload/Download Agent | | Write platform automation | references/python-sdk.md | dxpy | | Launch or debug execution | references/job-execution.md | dx run, dx watch, dxpy | | Import WDL, CWL, or Nextflow | references/workflow-languages.md | dxCompiler or dx build --nextflow | | Diagnose auth, cost, or failures | references/operations-and-troubleshooting.md | read-only inspection first |
Use dx upload and dx download for small sets. Use Upload Agent for multiple or large files (official guidance recommends it above 50 MB) and Download Agent for large or long-running batch downloads.
bashdx upload "sample.fastq.gz" \ --path "project-xxxx:/raw/sample.fastq.gz" \ --property "sample_id=S001" dx download "project-xxxx:/results/sample.bam" \ --output "sample.bam"
Upload Agent compresses uncompressed inputs by default and appends .gz. Use --do-not-compress when byte-for-byte preservation or the original name is required. See references/data-operations.md.
find_data_objects() uses exact name matching unless name_mode is supplied. Do not pass "*.bam" without name_mode="glob".
pythonimport dxpy files = dxpy.find_data_objects( classname="file", project="project-xxxx", folder="/results", recurse=True, name="*.bam", name_mode="glob", state="closed", describe={"fields": {"name": True, "size": True, "archivalState": True}}, limit=100, ) for result in files: description = result["describe"] print(result["id"], description["name"], description["archivalState"])
Bound broad searches with a project, folder, time range, and limit.
bashdx-app-wizard
Resolve bundled helpers relative to this skill directory. From the skill root:
bashuv run python "scripts/validate_dxapp.py" \ "/path/to/my-app/dxapp.json" --kind applet --strict
Then build the source directory:
bashdx build "/path/to/my-app"
For a versioned app, use the current build form:
bashdx build "/path/to/my-app" --create-app
New configurations should use Ubuntu 24.04 and regionalOptions.<region>.systemRequirements. Top-level resources and runSpec.systemRequirements in dxapp.json are deprecated. See references/configuration.md.
First inspect the executable:
bashdx run "applet-xxxx" -h
After target and cost confirmation:
bashdx run "applet-xxxx" \ --input-json-file "inputs.json" \ --destination "project-xxxx:/runs/run-001" \ --cost-limit 25
Keep the normal confirmation prompt for interactive use. Add --yes only in reviewed automation where the exact executable, project, inputs, destination, and cost policy are already approved.
bashdx find executions --created-after=-2h dx find jobs --state failed dx find analyses --created-after=-1d dx watch "job-xxxx" --get-streams
A run of an app or applet returns a job-...; a run of a workflow returns an analysis-.... dxpy.DXJob.wait_on_done() and dxpy.DXAnalysis.wait_on_done() can raise DXJobFailureError for remote failure, termination, or local wait timeout. Re-describe remote state before classifying it; see references/job-execution.md.
Use job-based output references:
pythonimport dxpy qc_job = dxpy.DXApplet("applet-qc").run( {"reads": dxpy.dxlink("file-input")}, project="project-xxxx", folder="/runs/run-001/qc", cost_limit=10, ) align_job = dxpy.DXApplet("applet-align").run( {"reads": qc_job.get_output_ref("filtered_reads")}, project="project-xxxx", folder="/runs/run-001/alignment", cost_limit=25, )
The downstream job remains waiting_on_input until the referenced output is ready. Do not wrap get_output_ref() in dxpy.dxlink().
24.04 for new work.
though the AEE sets PIP_BREAK_SYSTEM_PACKAGES=1; system/PyPI conflicts can otherwise produce DXExecDependencyError.
execDepends can drift. Prefer pinned asset bundles, bundleddependencies, or pinned containers for production.
instanceTypeSelector.allowedInstanceTypes and may require an organization license.
AppInsufficientResourceError requires both anexecution restart policy and the organization policy that permits instance upgrades.
Discover available instance types instead of copying a stale list.
file warning as a stop condition unless the user explicitly approves a safe containment workflow.
The commands below assume the current directory is this skill's root. Otherwise resolve scripts/ relative to the loaded skill directory.
dxapp.jsonbashuv run python "scripts/validate_dxapp.py" \ "path/to/dxapp.json" --kind app --strict
This offline validator catches structural mistakes, deprecated placement, broad access, and inconsistent regional requirements. It supplements, not replaces, dx build validation.
bashuv run --with "dxpy==0.410.0" \ "scripts/inspect_dxpy.py" --strict
This performs offline symbol and signature checks. It does not authenticate or make network calls.
references/authentication.md — login, tokens, environment precedence, andsecret handling
references/app-development.md — applet/app lifecycle, entry points,testing, build, and publication
references/configuration.md — current dxapp.json, regions, resources,dependencies, permissions, and retry policy
references/data-operations.md — transfers, search, metadata, cloning,archival, folders, and deletion
references/python-sdk.md — verified dxpy APIs and error handlingreferences/job-execution.md — jobs, analyses, monitoring, chaining, reuse,retries, and cost controls
references/workflow-languages.md — native workflows, WDL/CWL withdxCompiler, and Nextflow
references/operations-and-troubleshooting.md — operational playbooks andfailure diagnosis
references/sources.md — authoritative documentation and version baselineOther measured skills in the registry, with their headline benchmark lift.