User: DrAcula

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DrAcula0
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Posts by DrAcula

<prev • 5 results • page 1 of 1 • next >
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Tool: 3D UMAP and 3D tSNE visualization for Seurat
... **scRNAseq 3D Visualization Tool** I got a lot of help from these posts, Thought id share this tool for anyone working with a Seurat object to use for visualization: https://github.com/Dragonmasterx87/Interactive-3D-Plotting-in-Seurat-3.0.0/blob/master/3D%20UMAP%20Plotting%20v1.3.R Enjoy! ...
tool tsne scrnaseq 3d umap rna-seq written 8 days ago by DrAcula0
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Answer: A: Making a 3d tSNE Plot in Seurat for scRNA-seq
... I know this is old now. But Ive written some code which will help you create a 3D expression plot using plotly out of a seurat v3.0.0 object. Dont forget to star and fork :) Find the complete solution here: https://github.com/Dragonmasterx87/3D-Plotting-in-Seurat-3.0.0 Update: The code now support ...
written 4 months ago by DrAcula0
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How can you merge more than two 10x datasets in Seurat?
... I am trying to merge 3 datsets in seurat. I use the vignette on the seura website to merge 2 datasets however when I merge the 3rd t seems like the metadata isnt saved, however the head and tail of the data seem that its all being merged. ...
10x rna-seq scrnaseq written 7 months ago by DrAcula0 • updated 7 months ago by Charles Warden7.3k
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Comment: A: single cell RNAseq: From counts or RPKM > PCA > tSNE visualization of PCA
... I already have a csv file of genes and counts for my selected cells, How should I proceed?? ...
written 19 months ago by DrAcula0
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single cell RNAseq: From counts or RPKM > PCA > tSNE visualization of PCA
... Hello! I am a beginner at RNA seq analysis, I was hoping someone would point me in the direction of how I can take a data set (~50K genes in rows + 200 cells in columns, I have gene counts), perform a differential gene expression analysis (i don't know if this is needed for a PCA) and subsequently a ...
rna-seq written 19 months ago by DrAcula0

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Popular Question 7 months ago, created a question with more than 1,000 views. For single cell RNAseq: From counts or RPKM > PCA > tSNE visualization of PCA

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