Associate Professor 

Joshua Ho

Scalable bioinformatics methods for single cell data

Single cell RNA-seq and other high throughput technologies have revolutionised our ability to interrogate cellular heterogeneity, with broad applications in biology and medicine. Standard bioinformatics pipelines are designed to process individual data sets containing thousands of single cells. Nonetheless, data sets are increasing in size, and some biological questions can only be addressed by performing large-scale data integration. There is a need to develop scalable bioinformatics tools that can handle large data sets (e.g., with >1 million cells). Our laboratory has been developing scalable bioinformatics tools that make use of
modern cloud computing technology, fast heuristic algorithms, and virtual reality visualisation to support scalable data processing, analysis, and exploration of large single cell data. In this talk, we will describe some of these tools and their applications.

WORKSHOP: Single cell RNA-seq data analysis on the cloud

Computational processing of large single cell RNA-seq data has many challenges, including the scalable processing of tens to hundreds of gigabytes of data, using memory and CPU intensive computational programs. This can be especially challenging if
local computational resources are limited. Falco is a software bundle that enables bioinformatic analysis of large-scale transcriptomic data by utilising public cloud infrastructure. The framework currently provides supports for single cell RNA feature quantification, alignment and transcript assembly analyses. This workshop is a hands-on practical session on using Falco to run scalable bioinformatics analysis of single cell RNA-seq data.

Keywords: Cloud computing; Spark; RNA-seq; big data

Requirements: You will need to have an Amazon Web Service (AWS) account. Experience with working in the Unix command line environment is necessary.

Relevance: This workshop is relevant to anyone who are keen to explore the use of cloud computing for bioinformatics analysis, especially for single cell RNA-seq analysis.