Bioinformatics Spring School 2020


Bioinformatics Spring School 2020 is a week long training event for researchers, supported by Genomics Aotearoa and the New Zealand eScience Infrastructure (NeSI).

We will combine talks from researchers and hands on computational workshops (influenced by The Carpentries), covering example workflows of DNA variant calling, genotyping by sequencing (GBS), RNAseq analysis, and environmental DNA (eDNA).

This event is organised by Murray Cadzow, Ngoni Faya and Ludovic Dutoit.

When and where?

This is an in-person event.


This event will only cost your time (there isn’t a $ charge).



Is this for me?

This event is designed to give researchers (including students - 4th year and above) the opportunity to learn about and practice some bioinformatic skills. We’ll be covering bioinformatic workflows such as:

along with computational topics such as:

This week long event is designed to be an immersive experience so we ask that you commit to the entire week. We have chosen to interleave the computational topics throughout the week so that we can build on them throughout the entire week, so this ensures participants have the key knowledge at the right time.

The underlying workshop content is extremely similar to previous workshops run by Genomics Aotearoa so if you’ve already attended the Genomic Data Carpentry and RNAseq workshops you will have already covered the majority of the content.


Bioinformatic topics

DNA variant calling from next generation sequence data

Genotype-by-sequencing analysis (RAD-Sequencing)

RNA-sequencing differential expression analysis

Environmental DNA analysis

Computational Topics

These topics will be integrated into the bioinformatics workshops and built upon across the week with the goal of demostrating a best practices workflow approach to Bioinformatics analysis.

Introduction to the Unix command line (Bash)

Many bioinformatic programs will only operate in a Unix command line environment, as such we need to provide an introduction to working in this environment which will cover:

Introduction to R

Analysis portions of the workshops will be performed using R. As such we will provide a brief introduction to R. This will include:

Introduction to working in a high performance computing environment

We’ll be making use of the New Zealand eScience Infrastructure (NeSI), which is the national provider of high performance computing for researchers, to run our analysis and as part of this we’ll cover:

Introduction to version control using git

Running programs on the command line gives us the opportunity to save the commands used in scripts that we can reuse later on. It’s important that as we develop these scripts that we have a machanism to track the changes made. Git is a program that enables us to track the changes we make and see the differences between previous versions. The introduction to version control will cover:


Monday 23rd Nov

Time What
09:30 Welcome
10:00 Introduction to NeSI
10:45 Break
11:10 Introduction to BASH
12:15 Lunch
13:00 Keynote - Phil Wilcox
14:00 Introduction to BASH cont.
14:45 Break
15:00 Introduction to R
16:30 End of Day

Day 1 in-depth

Tuesday 24th Nov

Time What
09:30 Speaker
10:00 DNA variant calling
10:45 Break
11:00 DNA variant calling cont.
12:15 Lunch
13:00 DNA variant calling cont.
14:30 Break
14:45 DNA variant calling cont
16:30 End of Day

Wednesday 25th Nov

Time What
9:30 Speaker
10:30 Data101: From raw data to individual samples files
11:00 Break
11:15 Calling SNPs de-novo
12:15 Lunch
13:00 Calling SNPs de-novo, discussion
13:30 Calling SNPs with a reference genome
14:30 Break
15:00 Evolutionary Genetics basic toolbox (Population structure, Phylogenetic tree)
16:30 End of Day

Thursday 26th Nov

Time What
09:30 Speaker
10:00 RNAseq
10:45 Break
11:00 RNAseq cont.
12:15 Lunch
13:00 RNAseq cont.
14:30 Break
14:45 RNAseq cont.
16:30 End of Day

Friday 27th Nov

Time What
09:30 Symposium
10:30 Break
10:45 Experimental Design
11:00 QC and Denoising/Clustering
12:15 Lunch
13:00 Taxonomy Assignment
14:30 Afternoon Tea
14:45 Statistical Analysis
16:15 Course Summary
16:30 End of Day