Pacific Analytics

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Release Notes ​

This page documents the changes introduced in each version of PA Cloud.

Version 1.0.0-alpha.1 (2026-05-04) ​

Initial Alpha Release ​

This version introduces the core research and analysis ecosystem of Pacific Analytics. The platform is now open for end-to-end biological data exploration, from public data discovery to cloud-scale computation. We recommend limiting individual file uploads to 4GB during this alpha phase.

Research & Knowledge Management ​

Assistant & Sources ​

Ground your research using our AI Assistant, powered by a Retrieval-Augmented Generation (RAG) engine.

  • Knowledge Bases: Create "Sources" by uploading .pdf, .md, or .txt files. These are processed into embeddings for the Assistant to reference.
  • Agent Teams: Specialized AI agents (Nexus, Research Planner, etc.) are available to help with literature reviews and project planning.

Notebook & Scratchpad ​

Stay organized with integrated note-taking.

  • Scratchpad: A quick-access overlay for fleeting ideas.
  • Notebook: A full-screen manager for long-form documentation, fully synced with the Assistant's "Save to note" functionality.

Data Discovery & Storage ​

Nexus & Cohorts ​

Discover public data without leaving the platform.

  • SRA Integration: Search millions of samples from the Sequence Read Archive using dynamic, real-time filters.
  • Data Ingestion: Save cohorts and import FASTQ files directly into your project storage.

Datasets ​

A version-controlled file manager for your proprietary data.

  • Organization: Support for hierarchical folder structures and bulk folder uploads.
  • Integration: Easily attach datasets to sandboxes or reference them in workflow parameters using S3 URIs.

Computation & Analysis ​

Workflows ​

Execute production-grade pipelines at scale.

  • Nextflow Engine: Full support for Nextflow pipelines, including native integration with the nf-core suite.
  • Sample Sheets: Interactive metadata editor with auto-schema generation and cohort pre-filling for FASTQ data.
  • Monitoring: Live streaming logs and DRS-based output management.

Sandboxes ​

On-demand interactive compute environments.

  • IDEs: Choose between JupyterLab and VS Code.
  • Profiles: Specialized environments for Bioinformaticians (samtools, R, DESeq2) and Data Scientists (pandas, scikit-learn).
  • Attached Data: Mount any dataset or workflow output directly into your workspace for interactive post-analysis.

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