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Title: | VCFWeb: Aplicación web para el filtrado de variantes en formato VCF y diseño de estrategias para su priorización e integración con distintos tipos de datos |
Author: | Martín Lázaro, Alba |
Tutor: | Jiménez-García, Brian Sanchez-Cabo, Fatima |
Others: | Universitat Oberta de Catalunya Marco-Galindo, Maria-Jesús |
Abstract: | New DNA sequencing strategies, such as (NGS, Next-Generation Sequencing) allow geneticists to quickly identify genetic variations in many human genomes. However, being able to isolate a few variants that may be causative of disease continues to be a major challenge for medical genetics. The standard file format for containing variant calls is the VCF file (variant call format). This format is not easily manageable, since it contains very diverse information and it is difficult to represent the variants in a flat way. Furthermore, we work with large volumes of data, and resources are limited. Through the elaboration of a VCF file parser, obtained from the raw reads of sequences of different characteristics, a data structure is generated and it is exploited from a web tool, which is also developed as part of the project. As a result, an intuitive and efficient web application for CNIC researchers (National Center for Cardiovascular Research) has been obtained, as an attempt to reduce the number of variants as much as possible after passing through the filtering and prioritizing processes. The researcher will obtain, depending on the type of disease, a few candidate variants potentially causative of illness, and this will allow, on occasions, to take preventive measures before the first symptoms appear, being able in some cases to avoid or considerably reduce the disease. |
Keywords: | VCF web-based tool web applications |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2018 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
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File | Description | Size | Format | |
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amartinllaTFM0618memoria.pdf | Memoria del TFM | 3,05 MB | Adobe PDF | View/Open |
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