Spatial Omics Data Analysis with MAWA 4: Neighborhood Analysis using Spatial UMAP
When: Nov. 6th, 2024 11:00 am - 12:00 pm
Learning Level: Any
To Know
About this Class
Join Our Training on Spatial Omics Data Analysis with MAWA (Multiplex Analysis Web Apps).
Want to learn how to process and analyze your spatial proteomics/transcriptomics data? Join us for four virtual hour-long sessions at NIH, where you’ll get hands-on, step-by-step training using sample datasets (.csv, .tsv, .txt) with MAWA (Multiplex Analysis Web Apps). This user-friendly, graphical software platform offers an end-to-end solution for your analysis workflow following cell segmentation of your tissue.
What You’ll Learn:
- File Handling: Efficiently manage your datasets.
- Phenotyping: Identify and categorize cell types.
- Spatial Analysis: Analyze spatial relationships within your data.
Why Attend?
- Easy-To-Use Platform: MAWA offers an intuitive interface suitable for both novices and experts.
- High Performance: Efficiently handles large datasets with millions of cells or objects.
- Free Access: MAWA is available for free use.
Don’t miss this opportunity to enhance your data analysis skills with MAWA!
Planned schedule:
Tue 10/15, 1-2 PM
Topic: Introduction to NIDAP. MAWA Basics, and Supervised Phenotyping.
Speaker: Andrew Weisman, Ph.D.
Tue 10/22, 1-2 PM
Topic: Unsupervised phenotyping.
Speaker: Andrei Bombin, Ph.D.
Tue 10/29, 1-2 PM
Topic: Pairwise spatial analysis using hypothesis testing.
Speaker: Andrew Weisman, Ph.D.
Wed 11/6, 11-12 PM
Topic: Neighborhood analysis using spatial UMAP.
Speaker: Dante Smith, Ph.D.