BIOMSC X902 - Omics 4 Neuro - Single Cell and Spatial Omics, Data Mining
This three-day module introduces participants to the design, analysis, and strategic use of single cell and spatial omics data in neuroscience research.
Day 1 covers single cell omics, addressing experimental design considerations, platform selection, and key technical caveats; this will be followed by guided hands-on analysis of a single cell RNA-sequencing dataset in R using Seurat, using provided code templates, including quality control, normalization, clustering, cell type assignment, and differential expression. Day 2 addresses spatial transcriptomics, focusing on 10x Genomics Visium and Visium HD platforms and their application to a case study in Alzheimer's disease, with hands-on exploration in Loupe Browser and guided analysis in Seurat. Day 3 examines strategies for identifying and applying publicly available transcriptomic datasets and repositories to support grant applications and original research.
The module is intended for graduate students, postdoctoral researchers, staff, and faculty working with (or planning to work with) single cell or spatial transcriptomics data, and assumes upper-level coursework in genetics and molecular biology. No prior coding required: all scripts and code templates are provided.
Delivery Options
Hybrid: A learning experience that combines online coursework with in-person instruction, activities, or events. Participants complete designated online learning components and attend scheduled in-person sessions.
Time to Completion
This program is projected to take approximately 18 hours to complete.
Course Completion Requirements
Successful completion of this course requires earning a score of at least 99% on required assessments.
Technology Requirements
- Reliable internet connection
- Computer, laptop, or tablet capable of accessing online course materials
- Ability to stream video and interactive content
- Recommended browsers: Google Chrome or Firefox
Additional Technology Information
Access to the Ohio Supercomputer Center (OSC) and R/RStudio will be provided through our classroom project. A laptop with Loupe Browser pre-installed and course datasets pre-downloaded (shared via Carmen or OSC in advance). Instructions, datasets, tools, and scripts will be provided two weeks before the workshop.
Prerequisite Requirements
Upper-level coursework in genetics and molecular biology. We recommend reviewing the “Bulk Transcriptomics and Epigenomics”, “Single-cell Transcriptomics”, and “Spatial Transcriptomics” modules (available on Carmen) beforehand.
What You’ll Learn
- Know important considerations when designing single cell and spatial transcriptomics experiments.
- Run and interpret core analysis pipelines.
- Know where and how to find and apply public datasets to research questions.
What You’ll Earn
- A certificate of completion from Ohio State University College of Medicine.
Additional Information
Please note that tools should be accessed prior to the start of the in-person workshop. For assistance, reach out to Charlie.Campbell@osumc.edu.
Contact Us
For questions about the enrollment process, payment options, technology, or course records, please submit an inquiry and our Enrollment Support team will assist you within 24 hours during business days.
For questions about course details email COM_CCE@osumc.edu.