<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>CellMapper on Marius Lange</title><link>https://mariuslange.com/tag/cellmapper/</link><description>Recent content in CellMapper on Marius Lange</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>marius.lange.lab@gmail.com (Marius Lange)</managingEditor><webMaster>marius.lange.lab@gmail.com (Marius Lange)</webMaster><copyright>© 2026 Marius Lange. This work is licensed under [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/).</copyright><lastBuildDate>Thu, 08 May 2025 14:00:00 +0000</lastBuildDate><atom:link href="https://mariuslange.com/tag/cellmapper/index.xml" rel="self" type="application/rss+xml"/><item><title>🚀 Introducing CellMapper: Lightning-Fast Cell Mapping Across Datasets</title><link>https://mariuslange.com/post/cellmapper_release/</link><pubDate>Thu, 08 May 2025 14:00:00 +0000</pubDate><author>marius.lange.lab@gmail.com (Marius Lange)</author><guid>https://mariuslange.com/post/cellmapper_release/</guid><description>&lt;p&gt;Hey everyone! 👋 Bridging the gap between different single-cell datasets has always been challenging. Today I&amp;rsquo;m excited to unveil &lt;a href="https://github.com/quadbio/cellmapper" target="_blank" rel="noreferrer"&gt;CellMapper&lt;/a&gt;, a high-performance tool that makes this a bit easier through optimized k-NN transfer. Whether you&amp;rsquo;re mapping cell types from dissociated to spatial data, transferring embeddings between datasets, or identifying cellular niches, CellMapper makes these complex tasks both simple and blazingly fast. All you need it a joint embedding for your data, which you can get with methods like scVI, scArches, GLUE, scANVI, ENVI, MIDAS and many more, depending on the type of mapping problem.&lt;/p&gt;</description></item></channel></rss>