‘Bioinformatics for geneticists and biologists (BIGB02)

Delivered by Dr. Nic Blouin and Dr Ian Misner

http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-
biologists-bigb02/

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

Monday 3rd – Classes from 09:00 to 17:00
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.

Tuesday 4th – Classes from 09:00 to 17:00
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.

Wednesday 5th – Classes from 09:00 to 17:00
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.

Thursday 6th – Classes from 09:00 to 17:00
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.

Friday 7th – Classes from 09:00 to 16:00
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.

Please email any inquiries to [email protected] or visit our 
website www.prstatistics.com

Please feel free to distribute this material anywhere you feel is suitable

Upcoming courses - email for details [email protected]

1.      MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R 
(January 2017)
http://www.prstatistics.com/course/model-base-multivariate-analysis-of-
abundance-data-using-r-mbmv01/

2.      ADVANCED PYTHON FOR BIOLOGISTS (February 2017)
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/

3.      STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R 
(February 2017)
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-
simm03/

4.      NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017)
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/

5.      ADVANCES IN MULTIVAIRAITE ANALYSIS OF SPATIAL ECOLOGICAL DATA 
(April 2017)
http://www.prstatistics.com/course/advances-in-spatial-analysis-of-
multivariate-ecological-data-theory-and-practice-mvsp02/

6.      INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017)
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-
biologists-irfb02/

7.      ADVANCING IN STATISTICAL MODELLING USING R (April 2017)
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-
advr05/

8.      INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (May 2017)
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-
modelling-using-r-ibhm02/

9.      MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017)

10.     GEOMETRIC MORPHOMETRICS USING R (June)
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/

11.     BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017)
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-
biologists-bigb02/

12.     INTRODUCTION TO METHODS FOR REMOTE SENSING (July 2017)

13.     SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017)
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-
spae05/ 

14.     ECOLOGICAL NICHE MODELLING (October 2017)

15.     GENETIC DATA ANALYSIS USING R (October TBC)
16.     INTRODUCTION TO PYTHON FOR BIOLOGISTS (October TBC)
17.     INTRODUCTION TO BIOINFORMATICS USING LINUX (October TBC)
18.     LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November TBC)
19.     PHYLOGENETIC DATA ANALYSIS USING R (November TBC)

20.     APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS 
(November 2017)

21.     ADVANCING IN STATISTICAL MODELLING USING R (December 2017)

 
Oliver Hooker PhD.
PR statistics

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