Bioinformatics Tools for Next-Generation RNA Sequencing Analysis. Marconi, M., Rodriguez-Romero, J., Sesma, A., & Wilkinson, M., D. Sesma, A. & von der Haar, T., editors. Fungal RNA biology, pages 371-391. Springer International Publishing, 2014. ![Fungal RNA biology [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex The purpose of this chapter is to introduce the reader to some of the most popular bioinformatics tools and resources available for RNA analysis. The introduction of RNA next-generation sequencing led to an explosion in the amount of quantitative transcript sequence data, which necessitated the development of adequate tools to process and make a sense of these rich and complex datasets. A large number of programs, platforms, and databases dedicated to RNA analysis have been produced over the past approximately 20 years; however, like so much other bioinformatics software, only a small portion of them are still available and in-use. As such, we will focus only on those tools and applications still in common use. This chapter is composed of three sections: the description of the general protocols for RNA sequence (generically called RNA-Seq) analyses, an outline of the most common approaches to map polyadenylation sites, and a brief introduction to noncoding RNA (ncRNA) analysis. The first section will describe the composition of steps within a typical RNA-Seq study: the experimental design, the sequencing methods, the data quality control, the read mapping, and the differential expression analysis. The second section will introduce a few recent methods developed to map polyadenylation sites: the experimental protocols (which are variations of RNA-Seq), polyadenylation site databases and prediction programs, and cis-regulatory elements discovery. The third and final section will present several of the ncRNA databases and prediction tools.
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abstract = {The purpose of this chapter is to introduce the reader to some of the most popular bioinformatics tools and resources available for RNA analysis. The introduction of RNA next-generation sequencing led to an explosion in the amount of quantitative transcript sequence data, which necessitated the development of adequate tools to process and make a sense of these rich and complex datasets. A large number of programs, platforms, and databases dedicated to RNA analysis have been produced over the past approximately 20 years; however, like so much other bioinformatics software, only a small portion of them are still available and in-use. As such, we will focus only on those tools and applications still in common use. This chapter is composed of three sections: the description of the general protocols for RNA sequence (generically called RNA-Seq) analyses, an outline of the most common approaches to map polyadenylation sites, and a brief introduction to noncoding RNA (ncRNA) analysis. The first section will describe the composition of steps within a typical RNA-Seq study: the experimental design, the sequencing methods, the data quality control, the read mapping, and the differential expression analysis. The second section will introduce a few recent methods developed to map polyadenylation sites: the experimental protocols (which are variations of RNA-Seq), polyadenylation site databases and prediction programs, and cis-regulatory elements discovery. The third and final section will present several of the ncRNA databases and prediction tools.},
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