Pinned Loading

1. Seurat to Veloctyo Code -- This is a... Seurat to Veloctyo Code -- This is a general code chunk for running Velocyto on a Seurat object generated with 10x single-cell sequencing data.

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   library(velocyto.R)

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   library(pagoda2)

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   library(Seurat)

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   ### ASSUMES Seurat object has already been computed -- in this case the object cells.combined is the result of seurat

2. fastq-to-treat fastq-to-treat Public

   Handles the preprocessing from illumina fastq files through TREAT using SnakeMake

   Python 2

3. Seurat Split By - Corrected Scaling Seurat Split By - Corrected Scaling

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   wt.subset <- subset(immune.combined, subset = stim == c("CTRL"))

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   ko.subset <- subset(immune.combined, subset = stim == c("Trp63-"))

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   FeaturePlot(immune.combined,features = c("Foxi2","Foxc1"),split.by = "stim")

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4. multimodal-tcga-hnsc multimodal-tcga-hnsc Public

   Multimodal Analysis using cross-view tensor-product integration on TCGA Head and Neck Tumor samples

   R 1

5. Seurat to Phate to Seurat Seurat to Phate to Seurat

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   ### handles the Seurat to phate conversio

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   ### first, grab the input required for phate (here we are using the normalized data stored in Seurat

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   seurat_data <- as.data.frame(seurat.object@assays$RNA@data)

6. Seurat to Loupe Seurat to Loupe

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   library(Seurat)

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   ## Prep for 10x loupe browser inegration

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   seurat.object 

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   ### first we need to extract out the seurat cell barcodes and convert them back into Loupe space