Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/48597
Title: RAP: A Web Tool for RNA-Seq Data Analysis
Authors: D'Antonio, Mattia
Libro, Pietro
Picardi, Ernesto
Pesole, Graziano
Castrignanò, Tiziana 
Issue Date: 2021
Abstract: 
Since 1950 main studies of RNA regarded its role in the protein synthesis. Later insights showed that only a small portion of RNA codes for proteins where the rest could have different functional roles. With the advent of Next Generation Sequencing (NGS) and in particular with RNA-seq technology the cost of sequencing production dropped down. Among the NGS application areas, the transcriptome analysis, that is, the analysis of transcripts in a cell, their quantification for a specific developmental stage or treatment condition, became more and more adopted in the laboratories. As a consequence in the last decade new insights were gained in the understanding of both transcriptome complexity and involvement of RNA molecules in cellular processes. For what concerns computational advances, bioinformatics research developed new methods for analyzing RNA-seq data. The comparison among transcriptome profiles from several samples is often a difficult task for nonexpert programmers. Here, in this chapter, we introduce RAP (RNA-Seq Analysis Pipeline), a completely automated web tool for transcriptome analysis. It is a user-friendly web tool implementing a detailed transcriptome workflow to detect differential expressed genes and transcript, identify spliced junctions and constitutive or alternative polyadenylation sites and predict gene fusion events. Through the web interface the researchers can get all this information without any knowledge of the underlying High Performance Computing infrastructure.
URI: http://hdl.handle.net/2067/48597
ISBN: 978-1-0716-1306-1
DOI: 10.1007/978-1-0716-1307-8_21
Appears in Collections:B1. Contributo in volume (Capitolo o Saggio)

Files in This Item:
File Description SizeFormat
RAP_978-1-0716-1307-8_21.pdf1.57 MBAdobe PDFView/Open
Show full item record

Page view(s)

81
Last Week
1
Last month
2
checked on Apr 17, 2024

Download(s)

9
checked on Apr 17, 2024

Google ScholarTM

Check

Altmetric


All documents in the "Unitus Open Access" community are published as open access.
All documents in the community "Prodotti della Ricerca" are restricted access unless otherwise indicated for specific documents