Workshops

The 2019 ABACBS/GIW conference will be held in Sydney from 9-11th December. The COMBINE/AYRCOB Student Symposium will be on the 9th December. It will be preceded by the AMSI BioInfoSummer meeting from 2-7th December, making for an exciting concentration of bioinformatics and computational biology in Sydney at the end of the year.

As in previous years, the one day following the main conference (12th December) will be dedicated to workshops that are focused on specific technical areas of interest, often with a practical hands-on component. At past conferences, these have been extremely popular events, and many have sold out early.

Questions on the workshops should be emailed to natalie.twine@csiro.au and kitty.lo@sydney.edu.au

Costs

Full Day Workshop: $50 per person

Half Day Workshop: $40 per person

Location

University of Technology Sydney (UTS), Building 10 (CB10)

Google Map: https://goo.gl/maps/SXPhYTBZzC4AHFk87

Classrooms: CB10.03.480, CB10.03.470, CB10.03.450

GWAS, Machine Learning and the Cloud (Half Day)*

Convener: Dr. Natalie Twine, Dr. Arash Bayat

In this workshop, you will learn how to setup a Jupyter notebook on AWS cloud with VariantSpark and Hail installed. You will learn to develop a GWAS analysis pipeline including quality-control, GWAS and post GWAS analysis.

Proteomics Data Analysis Workshop (Half Day)*

Convener: Prof. Jürgen Cox

This workshop provides an introduction to the computational proteomics platform MaxQuant and the downstream bioinformatics platform Perseus. The first part provides theory and background information to the workflows and algorithms while the second part is hands-on and participants will be able to apply the tools to some real-world examples. Participants should bring Windows laptop computers to participate in the practical parts.

Snakemake Workshop (Half Day)*

Convener: Dr. Nathan Watson-Haigh

Recent years have seen a groundswell of support in the bioscience community for improved reproducibility of data analyses. Large analysis workflows are fragile ecosystems of software tools, scripts and dependencies. One solution to these issues is the use of a workflow management system such as Snakemake, capable of being executed across different computing environments (laptop/desktop to High Performance Computing).

Nathan will cover the core concepts of Snakemake with a focus on reimplementing a bash script for performing quality control, trimming and alignment of Illumina data against a reference sequence. In doing so, workshop attendees will be capable of starting to implement their own workflows following the workshop.

Prerequisites

  • Experience with at least 1 scripting language

  • Experience with the Linux command line

  • Internet enabled laptop with an SSH client installed

Clinical Bioinformatics Symposium (Half Day)*

Details to be confirmed.

Machine Learning Applications Using Amazon Cloud Workshop (Full Day)*

Convener: Staffs from Amazon Cloud

In this workshop participants learn to solve Machine / Deep Learning problems using the tools available in the Amazon Web Services (AWS) cloud. The development and application of machine learning models is a vital part of scientific and technical computing. Increasing model training data size generally improves model prediction and performance but deploying models at scale is a challenge.

Participants will learn to use Amazon SageMaker, a new AWS service that simplifies the machine learning process and enables training on cloud stored datasets at any scale.

Applications will include:

  • toy use case (e.g. MNIST Handwritten Digit Recognition)

  • More elaborate distributed / framework use case – getting further into the tech

  • genomics, 1000 genomes dataset

  • other biosciences or health related dataset

The workshop will be similar to a workshop previously run by Amazon, in which you could find out more details here: http://www.c3dis.com/1878

* The workshop will only run if more than 10 people registered. Full refund will be provided to all registrants if the workshop is cancelled due to low number of participants.