title: BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments.
abstract: BACKGROUND
  It 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.
  
  
  RESULTS
  BEAT 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.
  
  
  CONCLUSIONS
  Despite 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.
authors.affiliation: Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.
authors.forename: Arianna
authors.initials: A
authors.lastname: Consiglio
authors.forename: Massimo
authors.initials: M
authors.lastname: Carella
authors.forename: Giorgio
authors.initials: G
authors.lastname: De Caro
authors.forename: Gianfranco
authors.initials: G
authors.lastname: Delle Foglie
authors.forename: Candida
authors.initials: C
authors.lastname: Giovannelli
authors.forename: Giorgio
authors.initials: G
authors.lastname: Grillo
authors.forename: Massimo
authors.initials: M
authors.lastname: Ianigro
authors.forename: Flavio
authors.initials: F
authors.lastname: Licciulli
authors.forename: Orazio
authors.initials: O
authors.lastname: Palumbo
authors.forename: Ada
authors.initials: A
authors.lastname: Piepoli
authors.forename: Elena
authors.initials: E
authors.lastname: Ranieri
authors.forename: Sabino
authors.initials: S
authors.lastname: Liuni
mesh_terms: D017398:Alternative Splicing; D002292:Carcinoma, Renal Cell / Q000235:genetics; D015179:Colorectal Neoplasms / Q000235:genetics; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020407:Internet; D007680:Kidney Neoplasms / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*