Workshop 3 – Fundamentals Single-cell RNA-seq analysis

Description

Intended audience
Bioinformaticians with good experience in R (e.g. reading files, tidyverse, visualization, scripting). Experience with bulk RNA-seq analysis or other -omics analysis would be highly beneficial.

Synopsis
Single-cell RNA-seq experiment and analysis is entering a mature and exciting phase of research. Many investigators are starting to deploy this tool at large scales (millions of cells). This presents an opportunity for existing and new bioinformaticians to make valuable contributions.
In this workshop, we will present the fundamental analysis with best scientific practices. We will cover data import, quality control, standard preprocessing steps, cell type annotation and differential expression for single-cell RNA-seq.

Materials
Course slides and data used for demonstration.

Biography

Adaikalavan Ramasamy:

Adai holds a DPhil from University of Oxford with post-doctoral training from Imperial, Kings and University College London. He headed the Transcriptomics Core Facility in Jenner Institute where he was responsible for generating andanalyzing data from clinical trials of vaccine efficacy. He joined A*STAR in 2016as Principal Scientist where he provides consultancy and training.

Gokce Oguz:

Gokce, a SINGA scholar, obtained her PhD from the National University of Singapore. She joined A*STAR in 2019 and advanced to Senior Scientist. Amidst COVID-19 pandemic, she led the Digital Patient Information Management team in the Stronghold Diagnostics Lab. She is committed to women participation in science and actively volunteers in this area. She is the lead analyst in numerous bulk, singlecell and spatial transcriptomics projects and has trained 500+ scientists to date.