Göke Lab

I will present about transcriptomics data analysis at INCOB 2016. The workshop will cover RNA-Seq work flows and tools, highlight some recent directions in computational methods development, and discuss concepts of good experimental design (using examples of bad experimental design). The workshop is together with Anders Skanderup’s lab at GIS who will give an introduction into cancer genomics.

Transcriptomics handout slides download

Cancer Genomics slides download

InCoB 2016 Singapore, 21-23 September 2016

An introduction to transcriptomics and cancer genomics: tools, databases and workflows

21st September 2016 (Wednesday), 1700 – 1900 hrs

Jonathan GOKE (Genome Institute of Singapore, A*STAR, Singapore)
Anders Jacobsen SKANDERUP (Genome Institute of Singapore, A*STAR, Singapore)
Yu GUO (Genome Institute of Singapore, A*STAR, Singapore)

Summary

High-throughput next-generation sequencing (NGS) data has become an integral component in most fields of biology research. In this workshop we will give two distinct guided tours on how to effectively leverage NGS data for transcriptomics and cancer genomics research, respectively. In the first part, we will present a research case study on the analysis of differential expression and alternative splicing using RNA-Seq data. We will use this case study to introduce fundamental concepts of experimental design for transcriptomics studies (differential expression, splicing, single cell gene expression), and to give an overview of commonly used software, tools, and workflows. In the second part, we will introduce and motivate the use of whole genome sequencing in cancer research. We will present efficient and robust computational algorithms and workflows to identify cancer mutations and cancer genes from hundreds of tumor genomes. Specifically, we will highlight common sources of errors in tumor DNA data and how we can leverage statistical models to deal with noise in the data.