Data Science Training Program
October 16-October 17, 2023

Reuben Thomas

Associate Core Director

Michela Traglia

Statistician III

Ayushi Agrawal

Bioinformatician II

This 3-session workshop will focus on the analysis of single-cell RNA-Seq data, starting from raw count matrices and progressing to network analysis of single-cell datasets. You’ll analyze data using R.
 
Attendance at all three sessions is required.

  • October 16 :  9:00am-12:00pm: Loading data, quality control, normalization, feature selection, dimensionality reduction
  • October 16:  1:00-4:00pm: Dimensionality reduction (continued), clustering, finding marker genes
  • October 17: 1:00-4:00pm: Advanced discussion on normalization, differential analysis, and batch-correction

 
Requirements

  • Familiarity with R and RStudio (e.g., reading in files, working with lists and dataframes)
  • Some exposure to RNA-seq datasets


Advanced: This is an advanced workshop in the RNA-Seq Analysis series. Prior experience with RNA-Seq analysis is required. See introductory and intermediate workshops:

Visit the workshop site for more details and materials 

Details

Dates
October 16, 2023
9:00am–4:00pm
October 17, 2023
1:00pm–4:00pm
Location
Online
Audience
Gladstone and UCSF
Contact(s)





The Gladstone Data Science Training Program was started in 2018 to provide trainees with learning opportunities and hands-on workshops to improve their skills in bioinformatics and computational analysis. This program offers a series of workshops throughout the year to enable trainees to gain new skills and get support with their questions and data.

Diversity, Equity, and Inclusion

At Gladstone, we are committed to providing events and professional development activities that resonate with our community’s diverse members. Our goal is to develop creative programming that encompasses a wide variety of ideas and perspectives to inspire, educate, and engage with everyone within our walls.

We want to effect positive change through our events and activities by providing a platform for discussions on important topics related to increasing diversity and inclusiveness in the sciences.