Mac Singlecell

MAC terminal
common@h21 ~ % cd /Users/common/Documents/scRNAseq01
common@h21 scRNAseq01 % split -l 1000 ccRCC_scRNASeq_NormalizedCounts1.txt ccRCC_scRNASeq_NormalizedCounts1.txt.
common@h21 scRNAseq01 %

R studio

rm(, list = ls())
library(Seurat)

rawdata <- read.table(file = "/Users/common/Documents/scRNAseq01/rawdatasplit1000.txt",
header = T,
row.names = 1,
stringsAsFactors = F,
sep = "\t")

rawdata[1:5, 1:5]

ddseq <- CreateSeuratObject(counts = rawdata, project = "RCC")

ddseq@assays$RNA@data[1:5,1:5]
VlnPlot(ddseq, features = c("nFeature_RNA", "nCount_RNA"), ncol = 2)

ddseq <- FindVariableFeatures(ddseq, selection.method = "vst", nfeatures = 100)
top10 <- head(VariableFeatures(ddseq), 10)
plot1 <- VariableFeaturePlot(ddseq)
plot2 <- LabelPoints(plot = plot1, points = top10, repel = TRUE, xnudge = 0, ynudge = 0)
plot1+plot2

#scaling
all.genes <- rownames(ddseq)
ddseq <- ScaleData(ddseq, features = all.genes)

ddseq <- RunPCA(object = ddseq, features = VariableFeatures(object = ddseq))
VizDimLoadings(ddseq, dims = 1:2, reduction = "pca")
DimPlot(ddseq, reduction = "pca")
DimHeatmap(ddseq,dims = 1:5, cells = 500, balanced = T)

#dimensionality
ddseq <- JackStraw(ddseq, num.replicate = 100)
ddseq <- ScoreJackStraw(ddseq, dims = 1:20)
JackStrawPlot(ddseq, dims = 1:15)

#altanatively ,
ElbowPlot(ddseq)