Reference-free cell type deconvolution of spatial transcriptomics data with STdeconvolve
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- Опубликовано: 6 авг 2024
- I'm learning how to give + record my scientific talks from home. This video is an abbreviated version of invited scientific talks I have presented and continue to present at various scientific conferences for our work on reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data.
In addition to the main scientific talk, an introduction intended for a more general audience has been added. I hope this video will be able to serve as a useful reference for those interested in learning more about multi-cellular pixel-resolution spatially resolved transcriptomic data and associated computational analysis approaches.
To learn more about our work developing computational methods for analyzing spatially resolved transcriptomic data, please visit our lab website jef.works/ or follow me on Twitter / jefworks
To skip to parts of the talk you may be interested in:
- Introduction: • Reference-free cell ty...
- Technology background: • Reference-free cell ty...
- Clustering analysis: • Reference-free cell ty...
- Deconvolution analysis / Main talk: • Reference-free cell ty...
For additional information regarding the scientific paper referenced in this video, please see:
- Brendan F Miller, Feiyang Huang, Lyla Atta, Arpan Sahoo, Jean Fan^. Reference-free cell type deconvolution of pixel-resolution spatially resolved transcriptomics data. Nature Communications. 2022. www.nature.com/articles/s4146...
Beautifully put together slides and very exciting work! Thank you.
Amazing presentation 🤩. I loved how you made it easier to comprehend for anyone. Thank you 🙏. I hope to see more videos from you in the future 😊.
Deconvolution of cell type contributions of pixelsWITHIN a cell?
Does it work with Geomx data?
wow how does the deconvolution algorithm in 6:49 work? it looks SO much like a warren prell (brown university) paper