Join us in July and August to explore genome assembly, mRNA-Seq analysis, and Single-Cell analysis! We’re excited to follow up our three recent successful remote workshops with four more weeks of in-depth online education, complete with guest lectures from industry experts and one-on-one instructor assistance.
July 20 - July 23: Genome Assembly Workshop
This workshop, held once every two years, offers a unique opportunity to participate in an in-depth exploration of genome assembly, with instruction from experienced bioinformatics professionals from UC Davis and beyond. Join us for four days of hands-on learning over Zoom and Slack.
Genome Assembly is currently in a renaissance, with new technologies coming together to complement each other, producing high-quality reference grade assemblies. This remote workshop will focus on project design, library and sequencing technologies, genome assembly and data type integration process, and evaluation in a practical and informative setting. In addition to the experienced data analysts of the UC Davis Bioinformatics Core, this workshop will include guest lecturers from PacBio and Bionano to speak to the most recent developments in genome assembly. The hands-on portion of the workshop will involve command-line interaction with some R, therefore prior command-line and R experience is a must to participate.
July 27 - July 31: RNA-Seq Workshop
One of our most popular workshops— now online! This remote workshop will include a rich collection of lectures and hands-on sessions with individualized instructor support, covering both theory and tools associated with command-line RNA-seq data analysis. Participants will explore experimental design, cost estimation, data generation, and analysis of RNA-Seq data generated on the Illumina sequencing platform. Participants will explore software and protocols, create and modify workflows, and diagnose/treat problematic data utilizing high performance computing services. Exercises will be performed with provided datasets, using command-line interaction.
August 12-14: Introduction to Single Cell RNA-Seq
This distance learning workshop will cover experimental design, data generation, and analysis of single cell RNA sequencing data (primarily generated using the 10x platform) 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. The primary packages used for analysis will be 10x software (for sequence reads to counts) and the R packages (ex. Seurat) for downstream analysis.
There are no prerequisites other than basic familiarity with genomic concepts. Anyone with an interest in scRNA sequence analysis is welcome! Some familiarity with the command-line and R is helpful. However, we will dedicate some small amount of time to bringing everyone up-to-speed to be able to run the commands needed during this workshop.
Important Note: The single cell RNA-Seq workflows are specific to single cell experiments. If you will be conducting traditional RNA-Seq experiments using RNA isolated from tissues, blood, etc. you should attend our RNA-Seq workshop, which will be offered in July.
August 17-19: Advanced Single Cell RNA-Seq
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. Prior experience with the command line and R is a must to fully participate.
To learn more, and to register, visit https://registration.genomecenter.ucdavis.edu
