gravatar for vHelmholtz

3 hours ago by

United States

Hello,

I am following the integrated analysis of the Seurat tutorial using two datasets (GSE126783: control vs retinal degeneration). Could you let me know how to make an 'object.list' for the 'FindIntegrationAnchors' function?

## SETUP THE SEURAT OBJECT
# Load the PBMC dataset
ctrl.data <- Read10X(data.dir = ".../GEO/GSE126783/GSE126783_RAW/ctrl")
LD.data <- Read10X(data.dir = ".../GEO/GSE126783/GSE126783_RAW/LD")

# Initialize the Seurat object with the raw 
ctrl <- CreateSeuratObject(counts = ctrl.data, project = "O'Koren", 
          min.cells = 3, min.features = 200)
LD <- CreateSeuratObject(counts = LD.data, project = "O'Koren", 
          min.cells = 3, min.features = 200)

## NORMALIZING THE DATA
ctrl <- NormalizeData(ctrl, normalization.method = "LogNormalize", scale.factor = 10000)
LD <- NormalizeData(LD, normalization.method = "LogNormalize", scale.factor = 10000)

## IDENTIFICATION OF HIGHLY VARIABLE FEATURES (FEATURE SELECTION)
ctrl <- FindVariableFeatures(ctrl, selection.method = "vst", nfeatures = 2000)
LD <- FindVariableFeatures(LD, selection.method = "vst", nfeatures = 2000)

## PERFORM INTEGRATION ???

Below is the code in the Seurat tutorial. I will very much appreciate it if you help me to revise the code for the analysis.

data("ifnb")
ifnb.list <- SplitObject(ifnb, split.by = "stim")

ifnb.list <- lapply(X = ifnb.list, FUN = function(x) {
    x <- NormalizeData(x)
    x <- FindVariableFeatures(x, selection.method = "vst", nfeatures = 2000)
})

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modified 1 hour ago

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3 hours ago
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vHelmholtz20



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