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Bioinformatics and Statistics

The Data Science Initiative offers workshops and consultations that help you learn how to analyze data from bioinformatics or clinical research projects. We welcome questions about any stage of analysis from planning to presentation, regardless of your level of experience with data analysis. Our goal is to help you produce valid and reproducible results.

Meet our bioinformatics and statistics expert

Karla Lindquist
Karla Lindquist, PhD

Dr. Lindquist teaches and consults on topics related to statistics and bioinformatics, as well as programming in R. She also has expertise with shell scripting and other languages.

Supporting research and publishing

Dr. Lindquist guided a medical student on the statistical analysis for a recent publication in The Bone & Joint Journal. Mixed effects regression models were used to identify factors associated with developing complications after staged hip replacement surgeries. These findings will help clinicians and patients better prepare for these surgeries.

bone joint logo

Not sure what software to use?

Find helpful links for recommended software and high performance computer (HPC) resources, or check out our Help Center for a list of frequently asked data questions. Not able to find what you’re looking for? Contact us.

Keep up with bioinformatics and statistics at UCSF

Attend an upcoming data science workshop and stay up to date with the latest DSI news. Topics include clinical informatics, managing single cell RNA-seq data, and more. See the course catalog for a list of core DSI workshops and materials.

Upcoming workshops

Dr. Lindquist was very approachable and knowledgeable. I am a beginner to programming, and she thoroughly explained the statistical analyses and the scripts for analyzing my data in R. The DSI is a great resource for anyone looking to analyze, interpret, or present their experimental data.

Assistant Adjunct Professor in Pediatrics

How may we help you?

Contact us or search the Help Center for answers to frequently asked data science questions.

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