Data Science Training Program
April 15-April 18, 2022

Alex Pico

Director, Bioinformatics Core

Reuben Thomas

Associate Director, Bioinformatics Core

Min-Gyoung Shin and Ayushi Agrawal

Bioinformatician II

Michela Traglia

Statistician III

This three-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.

April 15, 2022 • 10am–12pm: Loading data, quality control, normalization, feature selection, dimensionality reduction
April 15, 2022 • 1–3pm: Dimensionality reduction (continued), clustering, finding marker genes
April 18, 2022 • 1–3pm: Advanced discussion on normalization, differential analysis, batch-correction, and Q&A


  • 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.

View the complementary workshops at UCSF.


April 15-April 18, 2022
10:00am-3:00pm PDT

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.