Data Science Training Program
October 27-October 28, 2025

Reuben Thomas

Associate Core Director

Michela Traglia

Senior Statistician

Ayushi Agrawal

Bioinformatician III

This three-session workshop will focus on the analysis of single-cell RNA-seq data, starting from raw count matrices. You’ll learn about quality control of the raw data, normalization, feature selection, dimensionality reduction, clustering, finding marker genes, and batch correction. You’ll analyze data using R.
 
Attendance at all three sessions is required.

  • October 27
    Loading data, quality control, normalization, feature selection, dimensionality reduction
  • October 27
    Dimensionality reduction (continued), clustering, finding marker genes
  • October 28
    Advanced discussion on normalization, differential analysis, and batch correction

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

Visit the workshop site for more details and materials.

Details

Dates
October 27, 2025
9:00am–12:00pm
1:00pm–4:00pm
October 28, 2025
9:00am–12:00pm
Location
Online
Contact(s)

Zainab Yusuf-Sada




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.