dnanexus-integration

You build and run genomics pipelines on DNAnexus by using the dxpy Python SDK to create applets, configure dxapp.json, and chain multi-step analyses. This automates uploading FASTQ inputs, executing jobs, and downloading BAM outputs.

To upload and download FASTQ, BAM, and VCF data objects, use dxpy to perform deterministic data transfers. This manages sequencing data as DNAnexus objects, organizing inputs and outputs by folders and metadata within your genomics pipeline.

Configuring dxapp.json involves defining your applet's inputs, outputs, and dependencies. You manage system packages and Docker-based assets within this configuration file to ensure deterministic execution of your genomics pipeline.

Yes, you can chain multi-step analyses and monitor job state by leveraging dxpy with job output references. This allows you to automate pipeline execution, track completion logs, and organize results sequentially.

DNAnexus integration supports Docker-based app execution and bundled dependencies. You define these system packages and assets within your dxapp.json configuration to create deployable executables for cloud genomics development.

Using dxpy for DNAnexus cloud genomics development removes the friction of manual data handling. It automates building executable apps, managing sequencing data objects, and reliably running end-to-end workflows deterministically.