🧪Trial version — For internal lab review only. Not for clinical or production use.

What the DMAC Provides

Capabilities & Standards

The Data Management and Analysis Core provides end-to-end data and bioinformatic infrastructure for systems immunology studies — from sample intake through reproducible analysis and public deposition — under a rigorous data governance framework.

Core Services

Sample & Metadata Management

Structured tracking of biological samples and study metadata across collaborating sites, with consistent identifiers and provenance from collection through analysis.

Two-Tier Quality Control

Quality control at the generating institution followed by independent DMAC validation before any dataset enters the platform — assay-aware checks for omic data types.

Multi-Omic Integration

Harmonization of transcriptomic, proteomic, metabolomic, and cytokine/chemokine data into analysis-ready resources for systems immunology research.

Reproducible Analysis Environments

Managed RStudio Server Pro environments on a cloud architecture so analyses are versioned, shareable, and reproducible across studies and team members.

Study Design Support

Reproducible randomization and power/sample-size analysis to support rigorous, well-powered study designs and transparent allocation.

Data Deposition

Publication of analyzed, de-identified datasets to public repositories including ImmPort and Gene Expression Omnibus, supporting open science mandates.

Data Governance & Standards

How we keep research data rigorous, secure, and trustworthy.

NIH Data Standards

Data are tracked, stored, and shared in accordance with National Institutes of Health data management and sharing expectations.

De-Identification & Privacy

Only de-identified data enter the platform. Sample-level and identifiable information are handled under institutional governance and never exposed publicly.

Secure Cloud Architecture

Infrastructure is built on Amazon Web Services with access controls appropriate to research data, separating public-facing content from protected datasets.

FAIR & Reproducibility

Workflows emphasize Findable, Accessible, Interoperable, and Reusable data, with versioned analysis environments so results can be independently reproduced.

Bring your study to ImmuneVISTA

The DMAC partners with investigators and consortia to manage, analyze, and share multi-omic data with rigor and reproducibility.