Summary of Sctree: Discovering Cellular Hierarchies in the Presence Of Batch Effects in Scrna-seq Data, by Moritz Vandenhirtz et al.
scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data
by Moritz Vandenhirtz, Florian Barkmann, Laura Manduchi, Julia E. Vogt, Valentina Boeva
First submitted to arxiv on: 27 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This novel method, scTree, combines single-cell Tree Variational Autoencoders with hierarchical clustering to tackle batch effects in RNA sequencing data. By learning a tree-structured representation, scTree corrects for biases and provides insights into complex cellular landscapes. In tests on seven datasets, scTree outperformed established methods, discovering underlying clusters and hierarchies. The learned hierarchy was analyzed for biological relevance, highlighting the importance of integrating batch correction in clustering procedures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Single-cell RNA sequencing helps us understand how cells work together. But when we combine data from different batches or experiments, it can be tricky to get a clear picture. scTree is a new way to group similar cells together while fixing this problem. It works by creating a tree-like structure that shows relationships between cells. scTree did better than other methods on seven datasets and helped us understand what’s happening at the cellular level. |
Keywords
» Artificial intelligence » Clustering » Hierarchical clustering
