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Building on material from Introduction to Single Cell RNA-Seq, this workshop aims to cover advanced topics, including TCR and trajectory analysis. Instruction in introductory analysis will not be provided.

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ucdavis-bioinformatics-training/2020-Advanced_Single_Cell_RNA_Seq

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All documentation for the workshop is best viewed from the github.io pages

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May 26, 2020 - May 28, 2020, 9 a.m. - 4:30 p.m daily. online learning

Aug. 17, 2020 - Aug. 19, 2020, 9 a.m. - 4:30 p.m daily. @ UC Davis

Contact - UC Davis Bioinformatics Core, training.bioinformatics@ucdavis.edu

This workshop will cover advanced topics in experimental design, data generation, and analysis of single cell RNA sequencing data on the command line and within the R statistical programming language. Participants will explore software and protocols, create and modify workflows, and diagnose/treat problematic data utilizing high performance computing services. Exercises will be performed on the command line and within R with a provided dataset.

Participants should be familiar with the material covered in Introduction to Single Cell RNA-Seq Analysis, including the use of the command line and R (see prerequisites section). Prior experience with the command line and R is a must to fully participate. If you would like to attend, listen and learn, that is OK, but we will be undable to train you in how to use the command line and R during this workshop.

There are no additional prerequisites other than basic familiarity with genomic concepts and single cell sequencing and analysis. This workshop will be held either online via Zoom (May workshop) or on the UCD campus (August workshop) and will run from 9:00am to 5:00pm each day with an hour break for lunch.

Participants must supply their own laptop/desktop with a reliable connection to the internet. The labtop/desktop should have a current versions of R version 4.0, Rstudio, and an application that allows them to ssh into a server (see this page)

FAQ

Who should attend? … Prior course participants have included faculty, post docs, grad students, staff, and industry researchers.

What are the prerequisites? … There are no prerequisites other than familiarity with general biological concepts and an enthusiasm for learning bioinformatics data analysis. Some familiarity with the command-line and R is desirable. However, we will dedicate time to bringing everyone up-to-speed to be able to run the commands needed during this workshop.

What do I need to bring? … You will need to bring your own laptop to use, and an application that will allow you to ssh into a server (e.g. Bash for windows, or terminal for Apple OSX). Computational exercises will be performed on a remote server. We can help with setup early on in the workshop. If your department does not allow you to install software on the laptop you’ll be bringing, please contact us ahead of time.

Can I bring my own data? … We will provide datasets for use during the workshop, as this helps to keep the workshop moving. There will be time, however, to discuss your own datasets and how you might work with them outside of the workshop.

How much does it cost? … The registration fee is $1,500 for current students, postdocs, staff and faculty at Univeristy of California campus' or UC National Labs (LBNL, LANL, LLNL), $1,750 for other academic or non-profit participants and $2,500 for other participants. We accept credit cards, as well as UC Davis recharge accounts, for payment.

How do I apply? … All registration is “first-come, first-served”. There is no application process. So, sign up as soon as possible to ensure your place in the workshop.

Where can I find more information, including your policies? ... Go to our website (bioinformatics.ucdavis.edu/training/) and check out our FAQ and Policies.

Questions

If you have any questions, please don’t hesitate to contact us at training.bioinformatics@ucdavis.edu

Register

For the remote/virtual course in May.

For the onsite UC Davis course in August.

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Building on material from Introduction to Single Cell RNA-Seq, this workshop aims to cover advanced topics, including TCR and trajectory analysis. Instruction in introductory analysis will not be provided.

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