‘Bioinformatics for geneticists and biologists (BIGB02)
Delivered by Dr. Nic Blouin and Dr Ian Misner
This course will run from 3rd – 7th July 2017 at SCENE Field Station, Loch Lomond, Glasgow
OVERVIEW The handling of large datasets has become intractable without some level of bioinformatic literacy. Many biologists find that there is a steep learning curve to develop the confidence required to explore their genomics datasets effectively. This bioinformatics short course includes a rich collection of hands-on instruction and lectures specifically intended to help novice users become comfortable with a range of tools currently used to analyse next-generation data.
INTENDED AUDIENCE The course is aimed at anyone interested in learning bioinformatics tools needed for handling large genomic datasets.
Course content is as follows
Day 1 Module 1: Linux. Linux is taught on the first day, this takes the entire day. Once you get through this portion you will be on your way to completing your own NGS analysis. We have created a workbook for this portion of the course. This is a step-by-step, or in the case, command-by-command, Linux guide. We complete each command as a class and discuss and review issues along the way.
Day 2 Module 2: RNAseq. We will cover two of the more popular tools in this workshop, The Tuxedo package & Trinity. Outcomes; Confidence to design effective RNAseq experiments. Knowledge of NGS sequencing platforms and their differing applications, ability to analyze Illumina data for quality and contamination. Proficiency to implement the Tuxedo package to analyze an RNAseq dataset.Create publication ready graphics with cummeRbund and EdgeR.
Day 3 Module 3: Assembly. Whether you have a reference genome or are working with de novo samples there are some basic tools and practices that we cover to help assist you in your genome project. In this module we will cover the basic metrics you should review when doing assembly as well as best practices to consider in your own project. Outcomes; Take raw reads through a complete assembly process. Working knowledge of different assembly issues/challenges. The effect of assembly settings on assembly outcomes.
Day 4 Module 4: Annotation. We will use MAKER and Blast2GO and annotate the genome we assembled in the assembly module. Outcomes; Understand the differences between functional and structural annotations. Train MAKER to improve structural annotations. Understand how MAKER improves with more evidence and training; visualize structural annotations. Apply functional annotations with Blast2GO.
Day 5 Module 5: Python. Why Python? In truth it doesn’t matter what coding language you learn but you should learn one. Python has a very straightforward syntax that is easy to understand.In this module we will utilise the clearly explained training examples from Python for Biologists. Outcomes; Understand Python language syntax. Create scripts to answer biological problems & parse and analyse BLAST outputs using custom Python code.
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