Data Science Training Program
February 9-February 10, 2023

Ayushi Agrawal, MS

Bioinformatician II, Bioinformatics Core

Michela Traglia, PhD

Statistician III, Bioinformatics Core

Reuben Thomas, PhD

Associate Core Director, Bioinformatic Core

Paulina Paiz

Research Associate I, Corces Lab

This 2-day hands-on workshop will provide an introduction to a typical single-cell ATAC-seq protocol and focus on the data analysis steps to address unique computational challenges before the downstream analysis.
You’ll learn how to perform quality checks of raw data in the typical format provided by sequencing centers, how to process the data, perform dimensionality reduction for visualization, clustering and cell type annotation, generate a gene score matrix to identify cell types, and perform motif and peak enrichment using ArchR. 
Attendance at both sessions is required.

  • Prior attendance at an scRNA-seq or bulk RNA-seq workshop, or experience with analysis of transcriptomics data
  • Familiarity with R and RStudio (e.g., reading in files, working with lists and dataframes)

Visit the workshop site for more details and materials.


February 9-February 10, 2023
1:00-4:00pm PST

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.