Single Cell Technologies and Analysis (Virtual)
The development of robust protocols sensitive enough to measure nucleic acids from single cells is revolutionising biology, enabling the interrogation of molecular mechanisms that are not evident from measurements that represent the average of thousands of cells.
Currently, established plate-based protocols (such as Smart-seq2) provide scalable and robust measurements of mRNA. However, technologies in this field are rapidly evolving, and have recently enabled RNA-seq to be conducted on thousands of single cells in parallel (e.g. 3’ end sequencing of mRNA in droplets) and for multiple classes of nucleic acid to be captured from the same cell (e.g. DNA and RNA with G&T-seq).
Reliable statistical methods for analysing these data are also being developed, though it can be difficult for those new to the field to identify the tools most suitable for the analysis of their data.
This exciting course is taught collaboratively by researchers from the Wellcome Sanger Institute. The programme will provide participants with a broad overview of established and cutting-edge single cell methodologies, practical experience in the relevant molecular biology and laboratory skills, and the computational and statistical skills needed to interpret these large data sets.
For more information and to register, visit the conference website
Enquiries to firstname.lastname@example.org
The course will provide virtual training in widely-applicable plate-based full-length mRNA sequencing (Smart-seq2) and an overview of performing higher throughput 3’ end based protocol (10x chromium/Drop-seq/Seq-well). The participants will also learn analysis of single-cell RNA-sequencing datasets including most widely used tools and methods.
The course will cover cell handling, flow cytometry (FACS) microfluidics systems and additional single-cell sequencing technologies. The integration of data analysis within the course will allow participants to critically evaluate both the technical performance and the biological interpretation of single cell data sets.
There will be a significant bioinformatics component in the course, as even primarily wet-lab based researchers need to understand the key QC metrics for single cell data to evaluate the data and any necessary protocol optimisations.
The programme will be complemented by distinguished guest speakers, who will present the latest research in this fast-moving field, along with opportunities for informal discussions.
- Lia Chappell, Wellcome Sanger Institute, UK
- Lira Mamanova, Wellcome Sanger Institute, UK
- Thierry Voet, Wellcome Sanger Institute, UK
- Kedar Natarajan, University of Southern Denmark
- Tallulah Andrews, Wellcome Sanger Institute
- Vladimir Kiselev, Wellcome Sanger Institute
- Sarah Teichmann, Wellcome Sanger Institute, UK
- Roser Vento, Wellcome Sanger Institute, UK
- Andrew Adey, OHSU Knight Cancer Institute, USA
- Omer Bayraktar, Wellcome Sanger Institute, UK
- Raheleh Rahbari, Wellcome Sanger Institute, UK