Infoscience

Journal article

Splicy: a web-based tool for the prediction of possible alternative splicing events from Affymetrix probeset data

BACKGROUND: The Affymetrix technology is nowadays a well-established method for the analysis of gene expression profiles in cancer research studies. However, changes in gene expression levels are not the only way to link genes and disease. The existence of gene isoforms specifically linked with cancer or apoptosis is increasingly found in literature. Hence it is of great interest to associate the results of a gene expression study with updated evidences on the transcript structure and its possible variants. RESULTS: We present here a web-based software tool, Splicy, whose primary task is to retrieve data on the mapping of Affymetrix probes to single exons of gene transcripts and displaying graphically this information projected on the gene physical structure.Starting from a list of Affymetrix probesets the program produces a series of graphical displays, each relative to a transcript associated with the gene targeted by a given probe. The information on the transcript-by-transcript and exon-by-exon mapping of probe pairs can be retrieved both graphically and in the form of tab-separated files. The mapping of single probes to NCBI RefSeq or EMBL cDNAs is handled by the ISREC mapping tables used in the CleanEx Expression Reference Database Project. We currently maintain these mappings for most popular human and mouse Affymetrix chips, and Splicy can be queried for matches with human and mouse NCBI RefSeq or EMBL cDNAs. CONCLUSION: Splicy generates probeset annotations and images describing the relation between the single probes and intron/exon structure of the target transcript in all its known variants. We think that Splicy will be useful for giving to the researcher a clearer picture of the possible transcript variants linked with a given gene and an additional view on the interpretation of microarray experiment data. Splicy is publicly available and has been realized in the framework of a bioinformatics grant from the Italian Cancer Research Association.

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