Data Science Training Program
Thursday, March 26, 2020

Krishna Choudhary, Gladstone Bioinformatics Core

Gene expression is central to cell biology. Disease pathways often involve changes in the expression levels of at least some genes. To quantify the expression levels, RNA-seq has become one of the most popular experimental methods. This hands-on workshop will provide an introduction to a typical bulk RNA-seq protocol and focus on the data analysis steps for recovering actionable insights.

We will start with raw data in the typical format that is provided by sequencing centers. We will process it by trimming adapters, mapping trimmed reads to a reference genome, tallying gene-wise counts, and end with differential gene expression analysis. We will also look at various methods of quality control at each step, learn to interpret data formats such as FASTQ, BAM, and GFF, and discuss the relevant tools and technology. No prior RNA-seq experience is required. Bring your laptop and power adapter!

Learning Path

NOVICE LEVEL: This is an introductory workshop in the RNA-Seq Analysis series. No prior experience required. No prerequisites.


March 26, 2020
2:00-5:00pm PDT
UCSF Mission Hall, Room 1407

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.

Getting There

UCSF Mission Hall, Room 1407

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.