Spatial Analysis and Quantifying Cell-to-Cell Interactions скачать в хорошем качестве

Spatial Analysis and Quantifying Cell-to-Cell Interactions

Go beyond the "cell count" and start analyzing the architecture of biology. In this session of the FS2K workshop, we move into Spatial Analysis, teaching you how to quantify how cells communicate and organize within tissues. Learn how to define complex neighborhoods and measure proximity between rare immune subsets and large anatomical structures. What you will learn: ☑️ Anatomical Context: Using Smoothed Features to help QuPath understand where a cell is located based on the characteristics of its neighbors. ☑️ The Proximity Metric: Running Signed Distance Transforms to measure exactly how many microns a T-cell is from a tumor or macrophage boundary. ☑️ Data Refinement: Identifying and deleting duplicate detections that occur when multi-nucleated cells overlap with standard segmentation. ☑️ Hotspot Analysis: Creating Density Maps to visually identify areas of high infiltration or metabolic activity. ☑️ Scientific Discovery: Exporting spatial data to Excel to calculate biological Enrichment Ratios. 00:00 - Introduction: Why Spatial Relationships Matter 01:31 - Accessing GitHub Instructions and Backup Projects 02:51 - Data Hygiene: Duplicating Projects Before Major Deletions 05:54 - Reloading Multi-Marker Object Classifiers 09:23 - Strategic Data Reduction for High-Plex Files 13:17 - Defining Irregular Morphologies: Tingible Body Macrophages 15:33 - Pixel Classifier Settings for Sprawling Cellular "Arms" 18:40 - Converting Detections to Annotations for Boundary Logic 20:46 - Troubleshooting Mac and Windows AI Path Issues 23:36 - Comparing Location-Based vs. Marker-Based Classification 25:55 - Optimizing Hardware: Why You Need a Mouse and Large Monitor 28:44 - Visualizing Data with Measurement Maps 31:19 - Intro to Smoothed Features: Learning from Neighbors 34:58 - Overtraining vs. Variable Importance Logs 38:32 - Measuring "Signed Distances" Between Cells and ROI 41:19 - Identifying and Deleting Overlapping/Duplicate Detections 45:45 - Applying Distance-Based Gating for "Touching" Cells 49:10 - Creating Multi-Positive Phenotype Thresholds (PD-1/Ki67) 57:32 - Building Heatmaps with Density Maps (Radius vs. Smoothing) 01:00:55 - Calculating Enrichment Ratios in Spreadsheets 01:05:40 - Statistical Probing: Is Cell Localization Random? 01:13:40 - Q&A and Resources for Further Learning Resources: Step-by-step tutorial: https://saramcardle.github.io/FS2K/Se... QuPath object hierarchy: https://qupath.readthedocs.io/en/0.6/... Download data and backup projects here: https://drive.google.com/drive/u/0/fo...