Abstract:In recent years, the introduction of new DNA sequencing
platforms dramatically changed the landscape of genetic studies. These
protocols for next-generation sequencing (NGS) are able to generate
massive amounts of data, requiring the creation of new computational
tools to deal with this data quickly and economically. With the
development of the RNA-Seq methodology, which uses the new sequencing
protocols to get information about RNA samples, the study of the
transcriptome gained a new boost. Problems such as the identification of
genes expression levels and alternative splicing can be solved with the
assembly and the study of the transcriptome. At the same time, the use
of this technology has the great advantage of allowing new biological
discoveries and observations. This technology has, however, the downside
of requiring a very considerable computational effort. This work aims to
present a detailed study about the problem of transcriptome alignment,
presenting an efficient computational solution, which requires the
development of heuristics to identify splice junctions using methods and
data structures for an efficient mapping.