GTDA16

Genomic and Transcriptomic Data Analysis

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   IMPORTANT DATES for this Course
   Deadline for applications: May 12th 2016
   Course dates: May 18th - May 20th 2016

Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants.

Instructors:

Francisco García is a biostatistician working in the Computational Genomics Department of the Centro de Investigación Príncipe Felipe (CIPF) in Valencia, where teh goal is to apply translational bioinformatics to personalised medicine integrating genomic and clinical data. His main research interests are: Statistical methods development for analysis and omic data integration from a Systems Biology perspective; Software development that allow converting data produced by the new high-throughput technologies (NGS, proteomics, metabolomics) into valuable, meaningful biomedical information that can be used for diagnostic, and prognostic purposes; Characterization of genetic variation in human populations by NGS.
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Affiliation: Department of Computational Genomics, Centro de Investigación Príncipe Felipe, Valencia (ES)

Alejandro Alemán is a bioinformatician working at the Computational Genomics Department in the Centro de Investigación Príncipe Felipe in Valencia, where the goal is to apply translational bioinformatics to personalised medicine integrating genomic and clinical data. He studied Computer Sciences at the University of Sevilla. I also holds a MSc degree in Bioinformatics and Computational Biology, and a MSc degree in Artifficial Intelligence. His main research interests are: development of pipelines and workflows for NGS data analysis; design and development bioinformatics applications for gene/variants prioritization and applications to manage NGS targeted sequencing data for diagnostic purposes; variation in the Spanish population.
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Affiliation: Department of Computational Genomics, Centro de Investigación Príncipe Felipe, Valencia (ES)

Course Description

This is a 3 day long theoretical and practical course on genomic data analysis. Questions such as How can I find the causative mutation of the disease in this family? What pathways are activated in my RNA-seq experiment? are becoming more frequent as Next Generation Sequencing (NGS) technologies are increasingly used in the laboratory. This activity has been designed to provide the researchers with the skills and tools to address these questions and many other ones related. The whole course is composed of two group of sessions that focus on the analysis of Genomic variation and Transcriptomics of Next Generation Sequencing Data. The genomics sessions review the different NGS technologies and their applications as well as the computational requirements of NGS-based projects. Following an introduction to NGS of genomes, exomes and panels, attendants will learn about NGS data quality issues, data pre-processing, how to compare sequenced reads with a reference genome and how to visualize the results in a genomic context. Then, the main aspects of genomic variant annotation, detection and prioritization of candidate variants will be covered. State-of-the-art software to assist in gene prioritization process will be used. Finally, NGS in the clinic will be reviewed with the use of panels of genes for precision diagnostic and the management of variants of uncertain effect. The transcriptomics sessions is devoted to transcriptomic studies (RNA-seq and miRNA-seq). After an introduction to NGS of transcriptomes, the attendants will learn to perform all the preprocessing steps to convert NGS reads into gene expression measurements. Then, gene expression data will be used to determine differential expression, to cluster expression patterns, or for building predictors. Functional profiling methodologies will be used to interpret the results according to gene ontology enrichment, network analysis, etc. Finally, sophisticated methods for pathway analysis of transcriptome profiles will be demonstrated. The Babelomics suite, a well-known package of gene expression analysis, will be used to illustrate. By the end of the course, participants will have acquired skills to interpret NGS data and to use multiple software tools for genetic variant detection and for transcriptomic studies.

Target audience

The course is oriented to experimentalists, end-users and PhD students who want to learn about the state-of-the-art of data analysis methodologies in this fast developing area. Students will acquire the necessary skills for analyzing their own data using known software packages (e.g. Babelomics). Lectures and hands-on sessions are taught in the facilities of the IGC, which provide the ideal environment for the organization of bioinformatic courses.

Pre-requisites

Experience in analyzing next generation data is an advantage, but not mandatory. The course does not require computer skills.

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:  Apr 22nd 2016