ABSTRACT
UNLABELLED: Protein-coding genes with multiple alternative polyadenylation sites can generate mRNA 3'UTR sequences of different lengths, thereby causing the loss or gain of regulatory elements, which can affect stability, localization and translation efficiency. 3USS is a web-server developed with the aim of giving experimentalists the possibility to automatically identify alternative 3 ': UTRs (shorter or longer with respect to a reference transcriptome), an option that is not available in standard RNA-seq data analysis procedures. The tool reports as putative novel the 3 ': UTRs not annotated in available databases. Furthermore, if data from two related samples are uploaded, common and specific alternative 3 ': UTRs are identified and reported by the server. AVAILABILITY AND IMPLEMENTATION: 3USS is freely available at http://www.biocomputing.it/3uss_server.
Subject(s)
3' Untranslated Regions , Gene Expression Profiling , Sequence Analysis, RNA , Software , InternetABSTRACT
The results of differential expression analyses provide scientists with hundreds to thousands of differentially expressed genes that need to be interpreted in light of the biology of the specific system under study. This requires mapping the genes to functional classifications that can be, for example, the KEGG pathways or InterPro families they belong to, their GO Molecular Function, Biological Process or Cellular Component. A statistically significant overrepresentation of one or more category terms in the set of differentially expressed genes is an essential step for the interpretation of the biological significance of the results. Ideally, the analysis should be performed by scientists who are well acquainted with the biological problem, as they have a wealth of knowledge about the system and can, more easily than a bioinformatician, discover less obvious and, therefore, more interesting relationships. To allow experimentalists to explore their data in an easy and at the same time exhaustive fashion within a single tool and to test their hypothesis quickly and effortlessly, we developed FIDEA. The FIDEA server is located at http://www.biocomputing.it/fidea; it is free and open to all users, and there is no login requirement.
