单细胞测序分析R包Seurat质量控制小提琴图QC VlnPlo

单细胞测序分析预处理结束，拿到原始count或者TPM文件后，我们到了下游分析处理环节。

Seurat包是单细胞入门普遍使用的下游分析R包，功能全面，官方网址：https://satijalab.org/seurat/

在一开始的质量控制QC步骤中，The percentage of reads that map to the mitochondrial genome 是一项QC标准，因为Low-quality / dying cells often exhibit extensive mitochondrial contamination 。

所以我们要挑出 MT genome，以下是官方给出的代码和小提琴图。

library(Seurat)
pbmc[["percent.mt"]] <- PercentageFeatureSet(pbmc, pattern = "^MT-")
# Visualize QC metrics as a violin plot
VlnPlot(pbmc, features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3)

官网 VlnPlot.png

我照着它做，结果MT都是0。

data.object[["percent.mt"]] <- PercentageFeatureSet(data.object, pattern = "^MT-")
VlnPlot(data.object, features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3)
Warning message:
In SingleExIPlot(type = type, data = data[, x, drop = FALSE], idents = idents,  :
  All cells have the same value of percent.mt.

wrong.png

仔细找了问题后，发现是annotation不统一，我的genome不是以‘MT-’开头的，修改后成功画出类似官网的图。

data.object[["percent.mt"]] <- PercentageFeatureSet(data.object, pattern = "^MT")
VlnPlot(data.object, features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3)

2.png