Data Management and Analysis Core

Core Leaders

Bernardo Lemos

DMAC Lead

Nirav C Merchant

Co-Lead

Tyson Swetnam

Co-Lead

Summary

The University of Arizona Superfund Research Program (UA SRP) will generate volumes and types of data that are not manageable in typical laboratory settings. The Data Management and Analysis Core (DMAC) will function as the primary service for UA SRP data management and analysis of large biological, geophysical, and chemical datasets, including but not limited to bulk and single cell RNA sequencing, geospatial coordinates and geochemical composition, analytical chemistry, and imaging. DMAC enables investigators by performing three core functions: (i) DMAC will lead the housing of all data in an easy-to-access data repository system: CyVerse. Cyverse is a computational infrastructure consisting of hardware, software, and personnel that are designed to handle huge datasets and complex analyses, and is maintained at the University of Arizona. DMAC will utilize a reference implementation (RI) that divides data into five different levels for easy data sharing, processing, and analyzing. Lowest levels (level 1) will be raw data, while higher levels (level 5) will be file formats utilizable in graphics visualizations. DMAC will support these processes with help from on-staff data analysts and bioinformaticians as well as CyVerse programmers who can devise analysis strategies for individual investigators. In addition to data storage, DMAC will orchestrate sample management using Fulcrum software. Fulcrum allows barcoding, global positioning, and annotation of biological samples in an easy-to-use application available on both traditional workstations and mobile platforms. (ii) Beyond data and sample management, DMAC will perform both standard and custom computational processing and analyses of data. In conjunction with UA SRP investigators, DMAC will apply traditional algorithms, or develop novel algorithms as needed, to identify signatures for the different data types collected. (iii) The storage and analytical capabilities of DMAC will be integrated into user-friendly web applications that allow individual investigators to retrieve, manipulate, and visualize UA SRP data. The web application will be implemented using an in-house maintained server in conjunction with the R statistical environment. DMAC is thus an integral component of the UA SRP proposal that utilizes state-of-the-art technologies to enable effective data management and the discovery of novel insights into arsenic exposure and its role in health and disease.

Access apps to analyze and visualize data at UA SRC Olympus Application Server.