Precision Medicine Bioinformatics: From raw genome and transcriptome data to clinical interpretation (PMBI01)
This course will run from the 29th October - 2nd November 2018 in Edinburgh and will be delivered by Dr. Malachi Griffith and Dr. Obi Griffith from Washington University.
Analysis of high throughput genome and transcriptome data is major component of many research projects ranging from large-scale precision medicine efforts to focused investigations in model systems. This analysis involves the identification of specific genome or transcriptome features that predispose individuals to disease, predict response to therapies, influence diagnosis/prognosis, or provide mechanistic insights into disease models. During this course (IBDR01), students will perform an example end-to-end bioinformatics analysis of genome (WGS and Exome) and transcriptome (RNA-seq) data. Students will start with raw sequence data for a hypothetical case, learn to install and use the tools needed to analyze this data on the cloud, and visualize and interpret results. After completing the course, students should be in a position to (1) understand raw sequence data formats, (2) perform bioinformatics analyses on the cloud, (3) run complete analysis pipelines for alignment, variant calling, annotation, and RNA-seq (transcriptome analysis approaches will be a major component of the workshop), (4) visualize and interpret whole genome, exome and RNA-seq results, (5) leverage the identification of passenger variants for immunotherapy applications, and (6) begin to place these results in a clinical context by use of variant knowledgebases. The data, tools, and analysis will be most directly relevant to human genomics and bioinformatics research. However, many of the skills and concepts covered will be applicable to other human diseases and model organisms. Furthermore, many analysis concepts covered during the workshop will be broadly applicable to other "big data" research problems. All course materials (including copies of presentations, practical exercises, data files, and example scripts prepared by the instructing team) will be provided electronically to participants.
This workshop is primarily aimed at researchers and technical workers with a background in biology who want to learn fundamental bioinformatics skills for genomics with a particular emphasis on biomedical research applications. The course is essentially a crash course in bioinformatics for next generation sequence data analysis. It would also be useful for students with a computational background who seek an introduction to genomics technology and analysis approaches. In general, it is suitable for anyone working with genome or transcriptome (RNA-seq) data in the context of disease research. Attendees are encouraged to bring their own data or project outlines for discussion. Some time during the course will be dedicated to consultation with a team of instructors from the McDonnell Genome Institute.
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