Event Date
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – Central Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Take your RNA-Seq analysis to the next level with single cell RNA-Seq. This technology allows insights with an unpredicted level of detail, but that brings a new level of complexity to the data analysis. In this course, we will learn about the most popular single cell platforms, how to plan a scRNA-Seq experiment, deal with some of the many pitfalls when analysing your data, and effectively gain exciting, and cell type specific biological insights
By the end of the course participants should:
Academics, post-graduate students or biotech employees working on, or planning to work on any type of single cell RNA-Seq data.
Delivered Remotely
Availability – 20
Duration – 2 days
Contact hours – Approx. 12 hours
ECT’s – Equal to 1 ECT’s
Language – English
Mixture of lectures covering the theory, and practical sessions using the Linux command line and RStudio. Practical sessions are a mixture of demonstrations by the tutor and exercises to be completed independently. Data sets for computer practical sessions will be provided by the instructors, but participants are welcome to bring their own data.
Participants should have a basic understanding of transcriptomics and molecular biology
Participants should have basic experience of R, RStudio and linux.
PLEASE READ – CANCELLATION POLICY
Cancellations/refunds are accepted as long as the course materials have not been accessed,.
There is a 20% cancellation fee to cover administration and possible bank fess.
If you need to discuss cancelling please contact oliverhooker@prstatistics.com.
Day 1 Classes from 9:30 – 3:30
Day 2 Classes from 9:30 – 3:30
Day 3 Classes from 9:30 – 3:30
Kathryn recently joined the Edinburgh Genomics team as the Genomics and Bioinformatics Training Coordinator. With a diverse background in bioinformatics and molecular biology, she specializes in phylogenetics and viral classification.