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. 2014 Jan;42(Database issue):D581-91.
doi: 10.1093/nar/gkt1099. Epub 2013 Nov 12.

PATRIC, the bacterial bioinformatics database and analysis resource

Alice R Wattam  1 , David Abraham, Oral Dalay, Terry L Disz, Timothy Driscoll, Joseph L Gabbard, Joseph J Gillespie, Roger Gough, Deborah Hix, Ronald Kenyon, Dustin Machi, Chunhong Mao, Eric K Nordberg, Robert Olson, Ross Overbeek, Gordon D Pusch, Maulik Shukla, Julie Schulman, Rick L Stevens, Daniel E Sullivan, Veronika Vonstein, Andrew Warren, Rebecca Will, Meredith J C Wilson, Hyun Seung Yoo, Chengdong Zhang, Yan Zhang, Bruno W Sobral
Affiliations

PATRIC, the bacterial bioinformatics database and analysis resource

Alice R Wattam et al. Nucleic Acids Res. 2014 Jan.

Abstract

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

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Figures

Figure 1.
Figure 1.
Integration and displays of different data types at the level of the gene. PATRIC provides various methods to search for individual genes that lead to a landing page where data are summarized (A) and also provides access to a variety of gene-centric tools and visualizations including a genome browser (B), the Compare Region viewer (C), a summary and filter mechanism for gene expression data (D) and a link to any structural data that might exist (D).
Figure 2.
Figure 2.
Comparative analysis tools at PATRIC. Researchers can use a variety of searches and browsers to find, select and save data to a private workspace, from which they deploy a number of comparative genomic analysis tools, including the Protein Family Sorter that has metadata filtering (A), heatmap summary of protein families (B), gene trees and multiple sequence alignments (C). The Comparative Pathway tool summarizes data from selected genomes across KEGG pathways (D). The Transcriptomic Data Analysis tool has both an expression and metadata filtering mechanism (F) that creates a gene list where data can be filtered to show up or down regulation (G) from which a heatmap view with advanced clustering capabilities of the data can be deployed (H). All analysis tools allow researchers to collect and refine data in their private workspace (E).
Figure 3.
Figure 3.
Data integration tools. PATRIC’s Disease View provides an interactive graph (A) that summarizes relationships between pathogens, the diseases they cause, and both host and pathogen genes associated with that disease. A collaboration with HealthMap that provides a global summary of geolocation reports showing disease-related information in real-time is also provided (B). The Protein Interaction Gateway collects data from public databases and allows researchers to examine data summarized at the taxon level (C), and also to look at individual PPIs with a sortable grid and node-edged graphs (D).
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