EzArray: a web-based highly automated Affymetrix expression array data management and analysis system

Abstract

Background: Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.

Results: EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.

Conclusion: EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from http://www.ezarray.com/.

Figure 1

EzArray is an Affymetrix expression array data management and analysis system. EzArray can be used to manage and share data including projects, samples, raw array data files, and analysis results. EzArray includes three highly automated and seamlessly integrated data analysis programs named PreQ for data preprocessing and quality assessment, ProS for data processing and statistical testing, and RepA for report generating and gene annotation. Express Analysis is a one-step data analysis tool that covers all processing procedures in PreQ, ProS, and RepA. Microarray data can be from users' experiments (Custom Array Data), published raw array data (deposited CEL supplementary files in GEO), or GEO curated DataSets (GDS records). In addition, a number of standalone tools have been included in EzArray, including tools for gene annotation, array probe search, R shell for interactive execution of R scripts, and R batch for batch execution of R scripts.

Figure 2

EzArray is a web-based system implemented with advanced web technologies. (A) A screenshot of the EzArray homepage. The most important navigation tool in EzArray is the menu bar under the EzArray logo. However, users can also use the Quick Start pull-down menus, the hyper-linked diagram, or the Quick Start links to get started. (B) Explorer-like online file management and group-based file sharing. While file owners have full control of their files (e.g. create new folders and files, rename or delete existing folders and files), group members can read, copy, and download others' files, but are not allowed to make changes. (C) Full-featured project search and browse tool. Users can browse project information page by page, update the viewing options, perform advanced searches, and download data in spreadsheet format. Similar tools are available for managing sample information and analysis results (not shown).

Figure 3

Express Analysis is a fully automated microarray data analysis program. (A) Users can search for GEO DataSets, download CEL supplementary files, and create EzArray projects to analyze previously published data. The sample information is automatically populated in the project based on the subset information stored in GEO GDS records. (B) Selecting samples to start new Express Analysis. While in most cases, default analysis methods and parameters can be used directly due to our built-in logics, experienced users have options to select methods and enter specific analysis parameters. Once the analysis is started, a pop-up window will appear showing currently running jobs. On the pop-up window, users can stop running jobs, remove failed jobs, or review finished jobs. In addition, users do not have to wait for results; instead, they can bookmark the page and come back later to review the results. (C) Example execution results from a run of Express Analysis with data shown in (B). The resulting files, including executed scripts and execution logs, are classified, listed, hyper-linked, and compressed in one file for easy downloading.