CPANG19 Computational PANGenomicsDownloadable poster in PDF |
IMPORTANT DATES for this Course
Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants. |
Instructors: |
Erik Garrison is a Postdoctoral
fellow at the University of California,Santa Cruz. His research has focused on the development of a software
toolkit for practical pangenomics: vg. He has eight years
of experience in genomics, where he has worked on the development of sequencing systems, participated in large scale
sequencing projects such as the 1000 Genomes Project,
and authored popular bioinformatics software such as the freebayes
variant caller. Raised in Kentucky, Erik obtained an undergraduate degree in the social sciences from Harvard University. After
graduation he worked at Harvard Medical School, One Laptop Per Child, and Boston College before beginning his studies at
the Sanger Institute.
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Mikko Rautiainen is a PhD student at the Max Planck Institute for Informatics. His doctoral work
consists of theoretical and practical work on graph genomes and various related topics, with a focus on
read alignment to graphs. His research includes projects such as genome assembly, read error correction
and RNA expression quantification. He is the author of GraphAligner,
a tool for aligning third generation sequencing reads such as Pacific Biosciences or Oxford Nanopore reads to sequence graphs. He graduated
from the University of Helsinki with a masters degree in computer science, has worked professionally for three years as a software developer
and now studies for a doctorate in bioinformatics at Saarbruecken.
Affiliation: Max Planck Institute for Informatics, Algorithms for Computational Genomics, Saarbrücken, DE |
Course Description
Reference genomes have become central to bioinformatics approaches, and form the core of standard analyses
using contemporary sequencing data. However, the use of linear reference genomes,
which provide the sequence of one representative genome for a species, is increasingly becoming a limitation
as the number of sequenced genomes grows. In particular, they tend to bias us away from the observation of
variation in the genomes we study. ObjectivesParticipants first will learn about limitations of linear reference-based methods and work through a brief refresher or introduction to standard approaches for processing sequencing data, including read alignment and variant calling. Provided these motivating examples, we will use data from a variety of relevant sources to develop an intuition about pangenomic methods and a practical familiarity with applicable tools. |
Target AudienceThis course is oriented towards biologists and bioinformaticians. The course will be of particular interest to researchers investigating organisms without a reference genome or populations featuring high levels of genetic diversity. |
Course Pre-requisites
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Detailed Program |
Instituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal Last updated: July 29th 2019 |