Brief Protocol for EDGE Bioinformatics: Analyzing Microbial and Metagenomic NGS Data
Casandra Philipson,
Karen Davenport,
Logan Voegtly,
Chien-Chi Lo,
Po-E Li,
Yan Xu,
Migun Shakya,
Regina Cer,
Kimberly Bishop-Lilly,
Theron Hamilton,
Patrick Chain
Affiliations
Casandra Philipson
Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, 8400 Research Plaza, Fort Detrick, MD, USADefense Threat Reduction Agency, Fort Belvoir, VA, USA
Karen Davenport
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Logan Voegtly
Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, 8400 Research Plaza, Fort Detrick, MD, USALeidos, 11955 Freedom Drive, Reston VA, USA
Chien-Chi Lo
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Po-E Li
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Yan Xu
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Migun Shakya
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Regina Cer
Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, 8400 Research Plaza, Fort Detrick, MD, USALeidos, 11955 Freedom Drive, Reston VA, USA
Kimberly Bishop-Lilly
Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, 8400 Research Plaza, Fort Detrick, MD, USA
Theron Hamilton
Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, 8400 Research Plaza, Fort Detrick, MD, USA
Patrick Chain
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Next-generation sequencing (NGS) offers unparalleled resolution for untargeted organism detection and characterization. However, the majority of NGS analysis programs require users to be proficient in programming and command-line interfaces. EDGE bioinformatics was developed to offer scientists with little to no bioinformatics expertise a point-and-click platform for analyzing sequencing data in a rapid and reproducible manner. EDGE (Empowering the Development of Genomics Expertise) v1.0 released in January 2017, is an intuitive web-based bioinformatics platform engineered for the analysis of microbial and metagenomic NGS-based data (Li et al., 2017). The EDGE bioinformatics suite combines vetted publicly available tools, and tracks settings to ensure reliable and reproducible analysis workflows. To execute the EDGE workflow, only raw sequencing reads and a project ID are necessary. Users can access in-house data, or run analyses on samples deposited in Sequence Read Archive. Default settings offer a robust first-glance and are often sufficient for novice users. All analyses are modular; users can easily turn workflows on/off, and modify parameters to cater to project needs. Results are compiled and available for download in a PDF-formatted report containing publication quality figures. We caution that interpreting results still requires in-depth scientific understanding, however report visuals are often informative, even to novice users.
