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      3USS: a web server for detecting alternative 3′UTRs from RNA-seq experiments

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          Abstract

          Summary: 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

          Contact: anna.tramontano@ 123456uniroma1.it

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references 16

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          MicroRNAs: target recognition and regulatory functions.

           David Bartel (2009)
          MicroRNAs (miRNAs) are endogenous approximately 23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes.
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            Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

            Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
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              NCBI GEO: archive for functional genomics data sets—update

              The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.
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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                01 June 2015
                22 January 2015
                22 January 2015
                : 31
                : 11
                : 1845-1847
                Affiliations
                1Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, 2Department of Physics, Sapienza University, Rome, Italy and 3Istituto Pasteur – Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: John Hancock

                Article
                btv035
                10.1093/bioinformatics/btv035
                4443675
                25617413
                © The Author 2015. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                Page count
                Pages: 3
                Categories
                Applications Notes
                Gene Expression

                Bioinformatics & Computational biology

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