<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/5304c0f09935476aa66b5c05da935a2a&quot; frameborder=&quot;0&quot; width=&quot;1664&quot; height=&quot;1248&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1248</height><width>1664</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1248</thumbnail_height><thumbnail_width>1664</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/5304c0f09935476aa66b5c05da935a2a-00001.gif</thumbnail_url><duration>89.89999999999998</duration><title>Co-pilot for Single-cell RNA Sequence Analysis</title><description>In this video, I introduce a co-pilot tool that I built for a regenerative medicine research lab at Harvard Medical School. The tool is designed to assist with single-cell RNA sequence analysis. I explain how it works, including how to plug in your unfinished analysis, select a language model, preview your analysis, and generate next steps. The tool queries a vector database of available methods on single-cell analysis and suggests the most relevant ones. I specifically focus on batch correction and provide guidance on using two relevant methods: scRNASequest and cytocipher.</description></oembed>