Assessing the impact of alternative splicing in cancer

• Autor(a) principal: Ana Catarina Gonçalves Gomes
• Data de Publicação: 2015
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/83101
• topic: Engenharia electrotécnica, electrónica e informática; Electrical engineering, Electronic engineering, Information engineering

Worldwide, millions of people live every day with a diagnosis of cancer. Alternative splicing is a process that happens in the early steps of transcription from DNA to RNA. In this process usually a single fragment of DNA can result in more than one transcript during which an aberrant mutation can occur and be the cause of a disorder. RNA-seq has been used nowadays, quite frequently, as a procedure to sequence genomes. RNA-seq performs the reconstruction of at least part of the genome of a patient from small fragments of it (reads), calculates the set of active genes and compares it with one from a reference person. This last step of active gene differentiation may help researchers to understand the original biological question that triggered the study. At this last stage it is also important to collect several kinds of information associated with the active genes in order to establish a solid base for informed decisions based on the process. Although the tools to achieve this evaluation do exist, usually they are dispersed causing the process to be difficult and slow. The whole process requires considerable computational resources and programming skills. Furthermore, it is important for the scientist to allow the visualization of the results and work with a user-friendly web interface. Our main purpose is to develop an application that helps researchers in this task of assessing the impact of alternative splicing in cancer by automating the full process from the reads analysis up to the results of alternative splicing analysis. To achieve those, the work includes the following tasks: develop a web interface to simplify the analysis process, assemble the existing iRAP pipeline and improving the gene enrichment step. Our contribution is four fold: make the whole process easy to use by the biologist expert; design and deploy the data analysis steps; extend an existing pipeline with module(s) specific for splicing; and apply our work in IPATIMUP's data on cancer. Automatization is the major contribution to improve efficiency and quality of the scientific research on the impact of alternative splicing in cancer.