Top Tweets for #embedsom
Really happy to see our efforts on #immunemonitoring of mice immunized with a semi-split inactivated #COVID19vaccine (EmCoVax) is out! We used 24 markers #spectralcytometry panel for #immunophenotyping of B & Tcells and #clustering using #EmbedSOM https://t.co/p45lDyjvVv

Here is the 2nd version of #EmbedSOM preprint:https://t.co/u2u2lfs2El This time with new parameters: importance, adjust, emcoord(for various layouting possibilities), smooth and 3D embedding(using z-dim). #SingleCell #clustering #cytometry #phdchat

Updated #EmbedSOM article is out on bioRxiv! https://t.co/w8j0LMSUnW
Now with bigger datasets, better embedding shape, 3D, etc.

3-D view of #EmbedSOM
Branches between #clusters from #singlecell #cytomtrydata are clearly visible using new "emcoords" parameter.
Try it:https://t.co/VsA5Bws37S
@__exa__ #EmbedSOM was presented at #vizbi by @Drbal_Lab. Looking forward to the second version of paper ๐ with new features! #SingleCell #CyTOF
@Drbal_Lab presents #EmbedSOM to #VIZBI audience. Looking forward to see more SOM-based dimensionality reduction analysis of diverse datasets in biology and in the outside world.

@Drbal_Lab presents #EmbedSOM to #VIZBI audience. Looking forward to see more SOM-based dimensionality reduction analysis of diverse datasets in biology and in the outside world.


Thanks to @SofieVanGassen from @saeyslab for introducing #EmbedSOM - a non linear embedding algo. by @__exa__ and @Drbal_Lab at German #CyTOF users meeting! Here is a GitHub link: https://t.co/x0FU7ukEqg and pre-print :https://t.co/bZBO3wi3QB

Our new preprint is out! #SingleCell #HighDimensional #Datavisualization using non-linear #embedding #algorithm #EmbedSOM-a #FlowSOM-trained embedding: faster than #tSNE nd #UMAP. A collabo. btwn @__exa__ from @IOCBPrague, @Drbal_Lab nd @CZphenogenomics . V welcome ur comments!
Rapid single-cell cytometry data visualization with EmbedSOM https://t.co/2S79qbhkvv #bioRxiv
#SingleCell high-dimensional #Datavisualization is a breeze with #EmbedSOM-a #FlowSOM-trained embedding: faster than #tSNE or #UMAP, check the video: https://t.co/QJEbmz83iF. The collaboration btwn @__exa__, @CharlesUniPRG, @IOCBPrague nd @CZphenogenomics. We welcome ur comments.
Rapid single-cell cytometry data visualization with EmbedSOM https://t.co/2S79qbhkvv #bioRxiv
#EmbedSOM tool for #cytometry in action
https://t.co/TXmP4cEPnP โฆ
Get your R package at https://t.co/koIGZq3kNW #rstats
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