BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments

Abstract

BackgroundIt is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.ResultsBEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza.To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis.ConclusionsDespite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

Integrated Exon Level Expression Analysis of Driver Genes Explain Their Role in Colorectal Cancer

“…Earlier methods have found exon level data to be more informative about the nature and level of transcripts [30] . Now with the knowledge that more than 90% of all genes undergo alternative splicing to produce more than one transcript for a gene, the potential of exon level data is being realized more than ever [31] – [33] . Gene centric approach for carrying out integrated analysis using aCGH and exon array data has yielded more of confirmatory results and lack the use of full potential of whole genome arrays [34] .…”

A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples

“…In general, the comparisons presented in Figure 5 show a considerable improvement using ESLiMc; even with respect to FIRMA that is probably the most widely used method [ 15 ]. There are many additional tools and bioinformatic applications that have been published to help in the analyses of exon arrays datasets, like easyExon [ 24 ] Exon-Array-Analyzer [ 25 ], AltAnalyze [ 26 ] and BEAT [ 27 ]; but most of them are not very innovative approaches because they usually are integrated software packages including standard statistical methods (such us ANOVA and SI) or including other known algorithms (such us FIRMA [ 15 ] and MADS [ 28 ]). One final comment about these tools is that several of them allow the usage of different probesets-to-gene mappings (core, extended or full) provided by Affymetrix for the exon arrays; and most methods recommend to use the “core” mapping for splicing detection.…”

The Investigation of Gene Regulation and Variation in Human Cancers and Other Diseases

“…The differentiation of neural progenitor cells can be visualized by staining for the neuronal marker class III betatubulin [51]. Alternative splicing of exons play an important role in cellular differentiation and pathogenesis [52]. Alternative splicing in colorectal cancer and renal cell cancer samples has been analyzed by the Bioinformatics Exon Array Tool (BEAT, http://beat.ba.itb.cnr.it/) using an Affymetrix GeneChip Exon Array [52].…”

“…Alternative splicing of exons play an important role in cellular differentiation and pathogenesis [52]. Alternative splicing in colorectal cancer and renal cell cancer samples has been analyzed by the Bioinformatics Exon Array Tool (BEAT, http://beat.ba.itb.cnr.it/) using an Affymetrix GeneChip Exon Array [52]. When the dataset was analyzed using GO terms, the cell differentiation (GO:0030154)-related gene delta-like 1 (Drosophila) (DLL1) was found to be involved in colorectal cancer [52].…”